
# Import all libraries in this cell
import requests
import numpy as np
import urllib.request
import pandas as pd
import csv
import geopandas as gpd
from bs4 import BeautifulSoup
import seaborn as sns
sns.set_style("darkgrid")
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('fivethirtyeight')  
import warnings
warnings.filterwarnings('ignore')


URL = "https://covid19.ncdc.gov.ng/"

#Get data from NCDC website
r = requests.get(URL)
soup = BeautifulSoup(r.content,'html.parser')


#print(soup.prettify())


# Selecting the table with the relevant data
table= soup.find('table', id='custom1')
#table


#Select the headers from the table
# headers = []
# for i in table.find_all('th'):
#     #print(i)
#     title = i.text.strip()
#     headers.append(title)
headers = [i.text.strip() for i in table.find_all('th') ]


headers

['States Affected',
 'No. of Cases (Lab Confirmed)',
 'No. of Cases (on admission)',
 'No. Discharged',
 'No. of Deaths']


def clean(j):
    row_data = j.find_all('td')
    row = [i.text.strip() for i in row_data]
    return row

scraped_data = [ clean(i) for i in table.find_all('tr')]

# scraped_data=[]
# for j in table.find_all('tr'): 
#     row_data = j.find_all('td')
#     row = [i.text.strip() for i in row_data]
#     #print(row)
#     scraped_data.append(row)


len(scraped_data)

38


scraped_data

[[],
 ['Lagos', '104,014', '871', '102,372', '771'],
 ['FCT', '29,464', '143', '29,072', '249'],
 ['Rivers', '18,044', '89', '17,800', '155'],
 ['Kaduna', '11,576', '11', '11,476', '89'],
 ['Oyo', '10,332', '3', '10,127', '202'],
 ['Plateau', '10,330', '3', '10,252', '75'],
 ['Edo', '7,923', '0', '7,601', '322'],
 ['Ogun', '5,810', '11', '5,717', '82'],
 ['Delta', '5,784', '502', '5,170', '112'],
 ['Kano', '5,339', '144', '5,068', '127'],
 ['Ondo', '5,173', '315', '4,749', '109'],
 ['Akwa Ibom', '5,004', '7', '4,953', '44'],
 ['Kwara', '4,691', '452', '4,175', '64'],
 ['Gombe', '3,313', '8', '3,239', '66'],
 ['Osun', '3,311', '29', '3,190', '92'],
 ['Enugu', '2,952', '13', '2,910', '29'],
 ['Anambra', '2,825', '46', '2,760', '19'],
 ['Nasarawa', '2,779', '395', '2,345', '39'],
 ['Imo', '2,678', '30', '2,590', '58'],
 ['Ekiti', '2,464', '6', '2,430', '28'],
 ['Katsina', '2,418', '0', '2,381', '37'],
 ['Benue', '2,317', '88', '2,204', '25'],
 ['Abia', '2,261', '-1', '2,228', '34'],
 ['Ebonyi', '2,064', '28', '2,004', '32'],
 ['Bauchi', '2,001', '10', '1,967', '24'],
 ['Borno', '1,629', '5', '1,580', '44'],
 ['Taraba', '1,478', '67', '1,377', '34'],
 ['Bayelsa', '1,364', '1', '1,335', '28'],
 ['Adamawa', '1,312', '134', '1,140', '38'],
 ['Niger', '1,183', '165', '998', '20'],
 ['Cross River', '919', '2', '892', '25'],
 ['Sokoto', '822', '0', '794', '28'],
 ['Jigawa', '669', '2', '649', '18'],
 ['Yobe', '638', '4', '625', '9'],
 ['Kebbi', '480', '10', '454', '16'],
 ['Zamfara', '375', '0', '366', '9'],
 ['Kogi', '5', '0', '3', '2']]


#Removing unwanted bracket from scraped data
scraped_data.remove([])


len(scraped_data)

37


scraped_data

[['Lagos', '104,014', '871', '102,372', '771'],
 ['FCT', '29,464', '143', '29,072', '249'],
 ['Rivers', '18,044', '89', '17,800', '155'],
 ['Kaduna', '11,576', '11', '11,476', '89'],
 ['Oyo', '10,332', '3', '10,127', '202'],
 ['Plateau', '10,330', '3', '10,252', '75'],
 ['Edo', '7,923', '0', '7,601', '322'],
 ['Ogun', '5,810', '11', '5,717', '82'],
 ['Delta', '5,784', '502', '5,170', '112'],
 ['Kano', '5,339', '144', '5,068', '127'],
 ['Ondo', '5,173', '315', '4,749', '109'],
 ['Akwa Ibom', '5,004', '7', '4,953', '44'],
 ['Kwara', '4,691', '452', '4,175', '64'],
 ['Gombe', '3,313', '8', '3,239', '66'],
 ['Osun', '3,311', '29', '3,190', '92'],
 ['Enugu', '2,952', '13', '2,910', '29'],
 ['Anambra', '2,825', '46', '2,760', '19'],
 ['Nasarawa', '2,779', '395', '2,345', '39'],
 ['Imo', '2,678', '30', '2,590', '58'],
 ['Ekiti', '2,464', '6', '2,430', '28'],
 ['Katsina', '2,418', '0', '2,381', '37'],
 ['Benue', '2,317', '88', '2,204', '25'],
 ['Abia', '2,261', '-1', '2,228', '34'],
 ['Ebonyi', '2,064', '28', '2,004', '32'],
 ['Bauchi', '2,001', '10', '1,967', '24'],
 ['Borno', '1,629', '5', '1,580', '44'],
 ['Taraba', '1,478', '67', '1,377', '34'],
 ['Bayelsa', '1,364', '1', '1,335', '28'],
 ['Adamawa', '1,312', '134', '1,140', '38'],
 ['Niger', '1,183', '165', '998', '20'],
 ['Cross River', '919', '2', '892', '25'],
 ['Sokoto', '822', '0', '794', '28'],
 ['Jigawa', '669', '2', '649', '18'],
 ['Yobe', '638', '4', '625', '9'],
 ['Kebbi', '480', '10', '454', '16'],
 ['Zamfara', '375', '0', '366', '9'],
 ['Kogi', '5', '0', '3', '2']]


headers

['States Affected',
 'No. of Cases (Lab Confirmed)',
 'No. of Cases (on admission)',
 'No. Discharged',
 'No. of Deaths']


#Creating a Data Frame For Scraped Data and Renaming Columns.
data = pd.DataFrame(scraped_data, columns=['states',
 'lab_confirmed_cases',
 'cases_on_admission',
 'discharged',
 'deaths'])


data.head()


data.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 37 entries, 0 to 36
Data columns (total 5 columns):
 #   Column               Non-Null Count  Dtype 
---  ------               --------------  ----- 
 0   states               37 non-null     object
 1   lab_confirmed_cases  37 non-null     object
 2   cases_on_admission   37 non-null     object
 3   discharged           37 non-null     object
 4   deaths               37 non-null     object
dtypes: object(5)
memory usage: 1.6+ KB


confirmed = "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"
recovered="https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv"
deaths= "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv"


urls= [confirmed, recovered, deaths]


#load csv files int dataframes
covid_data= [ pd.read_csv(i) for i in urls]


#unpack dataframes into variables
covid_confirmed, covid_recovered, covid_deaths=covid_data


#increase column width to 1500.
pd.options.display.max_columns=1500


covid_confirmed.head()


covid_deaths.head()


covid_recovered.head()


list_info= [covid_deaths, covid_recovered, covid_confirmed]
for i in list_info:
    i.info()
    print()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 289 entries, 0 to 288
Columns: 1002 entries, Province/State to 10/15/22
dtypes: float64(2), int64(998), object(2)
memory usage: 2.2+ MB

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 274 entries, 0 to 273
Columns: 1002 entries, Province/State to 10/15/22
dtypes: float64(2), int64(998), object(2)
memory usage: 2.1+ MB

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 289 entries, 0 to 288
Columns: 1002 entries, Province/State to 10/15/22
dtypes: float64(2), int64(998), object(2)
memory usage: 2.2+ MB


covid_external= pd.read_csv('./External_Data/covid_external.csv')


budget_data=pd.read_csv('./External_Data/Budget data.csv')


covid_external.head()


covid_external.shape

(37, 12)


covid_external.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 37 entries, 0 to 36
Data columns (total 12 columns):
 #   Column                   Non-Null Count  Dtype  
---  ------                   --------------  -----  
 0   states                   37 non-null     object 
 1   region                   37 non-null     object 
 2   Population               37 non-null     int64  
 3   Overall CCVI Index       37 non-null     float64
 4   Age                      37 non-null     float64
 5   Epidemiological          37 non-null     float64
 6   Fragility                37 non-null     float64
 7   Health System            37 non-null     float64
 8   Population Density       37 non-null     float64
 9   Socio-Economic           37 non-null     float64
 10   Transport Availability  37 non-null     float64
 11  Acute IHR                37 non-null     float64
dtypes: float64(9), int64(1), object(2)
memory usage: 3.6+ KB


budget_data.head()


data.columns

Index(['states', 'lab_confirmed_cases', 'cases_on_admission', 'discharged',
       'deaths'],
      dtype='object')


data.head()


#Removing commas from numerical data
data=data.replace(',','', regex=True)


data.head()


#Checking for null values
data.isnull().sum()

states                 0
lab_confirmed_cases    0
cases_on_admission     0
discharged             0
deaths                 0
dtype: int64


#Converting the numerical data to integers
str_to_int= ['lab_confirmed_cases','cases_on_admission', 'discharged', 'deaths' ]
for i in str_to_int:
    data[i]= data[i].astype('int64')


data.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 37 entries, 0 to 36
Data columns (total 5 columns):
 #   Column               Non-Null Count  Dtype 
---  ------               --------------  ----- 
 0   states               37 non-null     object
 1   lab_confirmed_cases  37 non-null     int64 
 2   cases_on_admission   37 non-null     int64 
 3   discharged           37 non-null     int64 
 4   deaths               37 non-null     int64 
dtypes: int64(4), object(1)
memory usage: 1.6+ KB


np.setdiff1d(data['states'], covid_external['states'])

array(['Cross River', 'Nasarawa'], dtype=object)


np.setdiff1d(covid_external['states'], data['states'])

array(['Cross river', 'Nassarawa'], dtype=object)


covid_external=covid_external.replace('Cross river', 'Cross River') #Replacing values


data=data.replace('Nasarawa','Nassarawa')


list_data= [covid_deaths, covid_recovered, covid_confirmed]


Daily_Data=[i[i['Country/Region']=='Nigeria'] for i in list_data]
# for i in list1:
#     a=i[i['Country/Region']=='Nigeria']
#     Daily_Data.append(a)


nigeria_timeseries= pd.concat(Daily_Data, axis=0)
nigeria_timeseries


#Renaming index
nigeria_timeseries=nigeria_timeseries.set_index([pd.Index(['deaths', 'recovered', 'confirmed'])])
nigeria_timeseries


#drop Province/State column
if 'Province/State' in nigeria_timeseries.columns:
    nigeria_timeseries.drop('Province/State', axis=1, inplace=True)


nigeria_timeseries


#Checking for Null Values
nigeria_timeseries.isnull().sum(axis=1)

deaths       0
recovered    0
confirmed    0
dtype: int64


nigeria_timeseries


nig_timeseries= nigeria_timeseries.T
nig_timeseries.head()


nig_timeseries=nig_timeseries[4:]
nig_timeseries.head()


nig=nig_timeseries.index


#create date column if not in the df
if 'dates' not in nig_timeseries.columns:
    nig_timeseries.insert(0, 'dates', nig)


nig_timeseries.head()


nig_timeseries.columns

Index(['dates', 'deaths', 'recovered', 'confirmed'], dtype='object')


create_list= list(range(0, len(nig_timeseries)))
#create list to use for df index


#set index with created list
nig_timeseries=nig_timeseries.set_index([(create_list)])


nig_timeseries.head()


#set date column to datetime data type
nig_timeseries['dates']= pd.to_datetime(nig_timeseries['dates'])


#convert numeric columns to integers
for i in ['deaths','recovered','confirmed']:
    nig_timeseries[i] =nig_timeseries[i].astype('int')


nig_timeseries.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 997 entries, 0 to 996
Data columns (total 4 columns):
 #   Column     Non-Null Count  Dtype         
---  ------     --------------  -----         
 0   dates      997 non-null    datetime64[ns]
 1   deaths     997 non-null    int32         
 2   recovered  997 non-null    int32         
 3   confirmed  997 non-null    int32         
dtypes: datetime64[ns](1), int32(3)
memory usage: 27.3 KB


#check the distribution of the data
data.hist(figsize=(10, 6));


data.nlargest(10, 'lab_confirmed_cases').plot.bar(x='states', y='lab_confirmed_cases')

<AxesSubplot: xlabel='states'>


data.nlargest(10, 'discharged').plot.bar(x='states', y='discharged');


data.nlargest(10, 'deaths').plot.bar(x='states', y='deaths');


#increase rows
pd.options.display.max_rows=1500


nig_timeseries.head(50)


#Get the actual covid data for each day
column_names =['deaths','recovered','confirmed']
new_column_names=['daily_death_count', 'daily_recovered_count', 'daily_confirmed_count']
def difference(a,b):
    nig_timeseries[b] = nig_timeseries[a].diff()
for i in range(len(column_names)):
    difference(column_names[i], new_column_names[i])


nig_timeseries.head(70)


nig_timeseries.shape

(997, 7)


nig_timeseries.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 997 entries, 0 to 996
Data columns (total 7 columns):
 #   Column                 Non-Null Count  Dtype         
---  ------                 --------------  -----         
 0   dates                  997 non-null    datetime64[ns]
 1   deaths                 997 non-null    int32         
 2   recovered              997 non-null    int32         
 3   confirmed              997 non-null    int32         
 4   daily_death_count      996 non-null    float64       
 5   daily_recovered_count  996 non-null    float64       
 6   daily_confirmed_count  996 non-null    float64       
dtypes: datetime64[ns](1), float64(3), int32(3)
memory usage: 50.6 KB


#nig_timeseries


#Check for erroneous values as a result of incorrect data input and set them to zero.
nig_timeseries.query('daily_confirmed_count < 0')


nig_timeseries.iloc[805:812]
#we can clearly see the error in row 811


#set the value at the position to 0.
nig_timeseries.daily_confirmed_count.iloc[811]=0


nig_timeseries.query('daily_death_count < 0')


nig_timeseries.iloc[865:870]


nig_timeseries.daily_death_count.iloc[869]=0


nig_timeseries.iloc[289:295]


nig_timeseries.daily_death_count.iloc[290]=0


nig_timeseries.query('daily_recovered_count < 0')


nig_timeseries.daily_recovered_count.iloc[560]=0


column_name =['deaths_moving_average','recovered_moving_average','confirmed_moving_average']
new_column_names=['daily_death_count', 'daily_recovered_count', 'daily_confirmed_count']
def moving_avg(a,b):
    nig_timeseries[a] = nig_timeseries[b].rolling(window=7).mean()
for i in range(len(column_name)):
    moving_avg(column_name[i], new_column_names[i])


plt.figure(figsize=(12, 6))
plt.title('Weekly Moving Average for Confirmed Covid Cases in Nigeria')
sns.lineplot(x='dates', y='confirmed_moving_average', data=nig_timeseries)
plt.xlabel('Dates')
plt.ylabel('Confirmed Cases')
plt.xticks(nig_timeseries.dates[::30], rotation='vertical')
plt.show()


plt.figure(figsize=(12, 6))
plt.title('Weekly Moving Average for Death Cases in Nigeria')
sns.lineplot(x='dates', y='deaths_moving_average', data=nig_timeseries)
plt.xlabel('Dates')
plt.ylabel('Death Cases')
plt.xticks(nig_timeseries.dates[::30], rotation='vertical')
plt.show()


plt.figure(figsize=(12, 6))
plt.title('Weekly Moving Average for Recovered patients in Nigeria')
sns.lineplot(x='dates', y=nig_timeseries['recovered_moving_average'].abs(), data=nig_timeseries)
plt.xlabel('Dates')
plt.ylabel('Recovered Cases')
plt.xticks(nig_timeseries.dates[::30], rotation='vertical')
plt.show()


nig_timeseries.head()


nig_timeseries['daily_confirmed_count'].max()

6158.0


nig_timeseries[nig_timeseries['daily_confirmed_count'] == nig_timeseries['daily_confirmed_count'].max()]


 covid_external.head(2)


data.head(2)


dataset=pd.merge(data, covid_external, on=['states'], how='inner')


dataset.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 37 entries, 0 to 36
Data columns (total 16 columns):
 #   Column                   Non-Null Count  Dtype  
---  ------                   --------------  -----  
 0   states                   37 non-null     object 
 1   lab_confirmed_cases      37 non-null     int64  
 2   cases_on_admission       37 non-null     int64  
 3   discharged               37 non-null     int64  
 4   deaths                   37 non-null     int64  
 5   region                   37 non-null     object 
 6   Population               37 non-null     int64  
 7   Overall CCVI Index       37 non-null     float64
 8   Age                      37 non-null     float64
 9   Epidemiological          37 non-null     float64
 10  Fragility                37 non-null     float64
 11  Health System            37 non-null     float64
 12  Population Density       37 non-null     float64
 13  Socio-Economic           37 non-null     float64
 14   Transport Availability  37 non-null     float64
 15  Acute IHR                37 non-null     float64
dtypes: float64(9), int64(5), object(2)
memory usage: 4.9+ KB


dataset.shape

(37, 16)


dataset.head()


dataset.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 37 entries, 0 to 36
Data columns (total 16 columns):
 #   Column                   Non-Null Count  Dtype  
---  ------                   --------------  -----  
 0   states                   37 non-null     object 
 1   lab_confirmed_cases      37 non-null     int64  
 2   cases_on_admission       37 non-null     int64  
 3   discharged               37 non-null     int64  
 4   deaths                   37 non-null     int64  
 5   region                   37 non-null     object 
 6   Population               37 non-null     int64  
 7   Overall CCVI Index       37 non-null     float64
 8   Age                      37 non-null     float64
 9   Epidemiological          37 non-null     float64
 10  Fragility                37 non-null     float64
 11  Health System            37 non-null     float64
 12  Population Density       37 non-null     float64
 13  Socio-Economic           37 non-null     float64
 14   Transport Availability  37 non-null     float64
 15  Acute IHR                37 non-null     float64
dtypes: float64(9), int64(5), object(2)
memory usage: 4.9+ KB


#Get top ten states by lab confirmed cases
line=dataset.nlargest(10, 'lab_confirmed_cases')


fig = plt.figure()

ax1 = fig.add_subplot(111)

ax1.plot('states', 'lab_confirmed_cases', data=line)

ax1.set_ylabel('Lab Confirmed Cases')

ax2 = ax1.twinx()

ax2.plot('states', 'Overall CCVI Index', 'r-',data=line)

ax2.set_ylabel('Overall CCVI Index', color='r')

for tl in ax2.get_yticklabels():
    
    tl.set_color('r')

plt.setp(ax1.xaxis.get_majorticklabels(), rotation=90)

plt.show()


dataset.columns

Index(['states', 'lab_confirmed_cases', 'cases_on_admission', 'discharged',
       'deaths', 'region', 'Population', 'Overall CCVI Index', 'Age',
       'Epidemiological', 'Fragility', 'Health System', 'Population Density',
       'Socio-Economic', ' Transport Availability', 'Acute IHR'],
      dtype='object')


correlation=dataset[['lab_confirmed_cases', 'cases_on_admission', 'discharged',
       'deaths', 'Population', 'Overall CCVI Index', 'Age',
       'Epidemiological', 'Fragility', 'Health System', 'Population Density',
       'Socio-Economic', ' Transport Availability', 'Acute IHR']].corr()


plt.figure(figsize=(10,6))
sns.heatmap(correlation.corr(), annot= True)

<AxesSubplot: >


# Getting the difference between the initial and revised budget. 
budget_data['difference']= budget_data['Initial_budget (Bn)']- budget_data['Revised_budget (Bn)']
budget_data.head()


#Percentage Variation from original Budget
budget_data['percent'] = ((budget_data['difference'] / budget_data['Initial_budget (Bn)']) * 100).round(2)
budget_data.head()


#State with the Highest variation in Budget.
budget_data['percent'].max()

86.63


budget_data[budget_data['percent'] == budget_data['percent'].max()]


#State with the lowest variation in Budget
budget_data['percent'].min()

12.7


budget_data[budget_data['percent'] == budget_data['percent'].min()]


# Top 10 States with the highest variation in Original budget


top10_highest = budget_data.nlargest(10, 'percent')


top10_highest


#plt.figure(figsize=(10,6))
sns.barplot(y='states', x='percent',
    data= top10_highest);


# Top 10 States with smallest variation in original budget


top10_low = budget_data.nsmallest(10, 'percent')
top10_low


#plt.figure(figsize=(14,6))
sns.barplot(y='states', x='percent',
    data= top10_low);


geo_nig = gpd.read_file('./Nig_geojson.json')


#geo_nig


geo_nig.explore()


geo_nig.head()


geo_nig.shape

(37, 13)


Geo_nig=geo_nig[['admin1Name', 'Shape_Leng','Shape_Area', 'geometry']]


Geo_nig.columns=['states', 'Shape_Length', 'Shape_Area', 'geometry']


Geo_nig.head()


Geo_nig.info()

<class 'geopandas.geodataframe.GeoDataFrame'>
RangeIndex: 37 entries, 0 to 36
Data columns (total 4 columns):
 #   Column        Non-Null Count  Dtype   
---  ------        --------------  -----   
 0   states        37 non-null     object  
 1   Shape_Length  37 non-null     float64 
 2   Shape_Area    37 non-null     float64 
 3   geometry      37 non-null     geometry
dtypes: float64(2), geometry(1), object(1)
memory usage: 1.3+ KB


#Relace state names so we can join with data table
Geo_nig= Geo_nig.replace(['Federal Capital Territory', 'Nasarawa'], ['FCT', 'Nassarawa'])


Geo_nig


data.head()


Geo_nig=pd.merge(Geo_nig, data, on=['states'], how='inner') #combining the data table and the geo_nig table


Geo_nig.head()


Geo_nig.explore(column='lab_confirmed_cases',cmap='plasma',scheme='Percentiles', legend=True, tooltip=['states','lab_confirmed_cases','cases_on_admission','deaths'])


Geo_nig.explore(column='deaths',cmap='plasma', scheme='Percentiles',legend=True, tooltip=['states','lab_confirmed_cases','cases_on_admission','deaths'])


Geo_nig=pd.merge(Geo_nig,covid_external[['states', 'region', 'Population']] , on=['states'], how='inner')


Geo_nig[Geo_nig['region']=='South South']


Geo_nig.at[10, 'region']='South East' #Setting the correct region


Geo_nig.at[2, 'region']='South South' #Setting the correct region


Geo_nig[Geo_nig['states']=='Ebonyi']['region'] #Checking if the changes has been effected.

10    South East
Name: region, dtype: object


south_south=(Geo_nig[Geo_nig['region']=='South South']).reset_index()


south_south.head()


south_south.explore(column='deaths',cmap='viridis', scheme='quantiles',legend=True, tooltip=['states','lab_confirmed_cases','cases_on_admission','deaths'])
# for i in range(len(south_south)):
#      plt.text(south_south.Longitude[i],south_south.Latitude[i],"{}\n{}".format(south_south.states[i], south_south.deaths[i]),size=16, color='r')
# plt.title('COVID-19 Deaths by States for the South South.',fontsize=25)
# plt.show()


from subprocess import call
call(['python', '-m', 'nbconvert', 'covidproject.ipynb'])

1

	Province/State	Country/Region	Lat	Long	2/24/20	2/25/20	2/26/20	2/27/20	2/28/20	2/29/20	3/1/20	3/2/20	3/3/20	3/4/20	3/5/20	3/6/20	3/7/20	3/8/20	3/9/20	3/10/20	3/11/20	3/12/20	3/13/20	3/14/20	3/15/20	3/16/20	3/17/20	3/18/20	3/19/20	3/20/20	3/21/20	3/22/20	3/23/20	3/24/20	3/25/20	3/26/20	3/27/20	3/28/20	3/29/20	3/30/20	3/31/20	4/1/20	4/2/20	4/3/20	4/4/20	4/5/20	4/6/20	4/7/20	4/8/20	4/9/20	4/10/20	4/11/20	4/12/20	4/13/20	4/14/20	4/15/20	4/16/20	4/17/20	4/18/20	4/19/20	4/20/20	4/21/20	4/22/20	4/23/20	4/24/20	4/25/20	4/26/20	4/27/20	4/28/20	4/29/20	4/30/20	5/1/20	5/2/20	5/3/20	5/4/20	5/5/20	5/6/20	5/7/20	5/8/20	5/9/20	5/10/20	5/11/20	5/12/20	5/13/20	5/14/20	5/15/20	5/16/20	5/17/20	5/18/20	5/19/20	5/20/20	5/21/20	5/22/20	5/23/20	5/24/20	5/25/20	5/26/20	5/27/20	5/28/20	5/29/20	5/30/20	5/31/20	6/1/20	6/2/20	6/3/20	6/4/20	6/5/20	6/6/20	6/7/20	6/8/20	6/9/20	6/10/20	6/11/20	6/12/20	6/13/20	6/14/20	6/15/20	6/16/20	6/17/20	6/18/20	6/19/20	6/20/20	6/21/20	6/22/20	6/23/20	6/24/20	6/25/20	6/26/20	6/27/20	6/28/20	6/29/20	6/30/20	7/1/20	7/2/20	7/3/20	7/4/20	7/5/20	7/6/20	7/7/20	7/8/20	7/9/20	7/10/20	7/11/20	7/12/20	7/13/20	7/14/20	7/15/20	7/16/20	7/17/20	7/18/20	7/19/20	7/20/20	7/21/20	7/22/20	7/23/20	7/24/20	7/25/20	7/26/20	7/27/20	7/28/20	7/29/20	7/30/20	7/31/20	8/1/20	8/2/20	8/3/20	8/4/20	8/5/20	8/6/20	8/7/20	8/8/20	8/9/20	8/10/20	8/11/20	8/12/20	8/13/20	8/14/20	8/15/20	8/16/20	8/17/20	8/18/20	8/19/20	8/20/20	8/21/20	8/22/20	8/23/20	8/24/20	8/25/20	8/26/20	8/27/20	8/28/20	8/29/20	8/30/20	8/31/20	9/1/20	9/2/20	9/3/20	9/4/20	9/5/20	9/6/20	9/7/20	9/8/20	9/9/20	9/10/20	9/11/20	9/12/20	9/13/20	9/14/20	9/15/20	9/16/20	9/17/20	9/18/20	9/19/20	9/20/20	9/21/20	9/22/20	9/23/20	9/24/20	9/25/20	9/26/20	9/27/20	9/28/20	9/29/20	9/30/20	10/1/20	10/2/20	10/3/20	10/4/20	10/5/20	10/6/20	10/7/20	10/8/20	10/9/20	10/10/20	10/11/20	10/12/20	10/13/20	10/14/20	10/15/20	10/16/20	10/17/20	10/18/20	10/19/20	10/20/20	10/21/20	10/22/20	10/23/20	10/24/20	10/25/20	10/26/20	10/27/20	10/28/20	10/29/20	10/30/20	10/31/20	11/1/20	11/2/20	11/3/20	11/4/20	11/5/20	11/6/20	11/7/20	11/8/20	11/9/20	11/10/20	11/11/20	11/12/20	11/13/20	11/14/20	11/15/20	11/16/20	11/17/20	11/18/20	11/19/20	11/20/20	11/21/20	11/22/20	11/23/20	11/24/20	11/25/20	11/26/20	11/27/20	11/28/20	11/29/20	11/30/20	12/1/20	12/2/20	12/3/20	12/4/20	12/5/20	12/6/20	12/7/20	12/8/20	12/9/20	12/10/20	12/11/20	12/12/20	12/13/20	12/14/20	12/15/20	12/16/20	12/17/20	12/18/20	12/19/20	12/20/20	12/21/20	12/22/20	12/23/20	12/24/20	12/25/20	12/26/20	12/27/20	12/28/20	12/29/20	12/30/20	12/31/20	1/1/21	1/2/21	1/3/21	1/4/21	1/5/21	1/6/21	1/7/21	1/8/21	1/9/21	1/10/21	1/11/21	1/12/21	1/13/21	1/14/21	1/15/21	1/16/21	1/17/21	1/18/21	1/19/21	1/20/21	1/21/21	1/22/21	1/23/21	1/24/21	1/25/21	1/26/21	1/27/21	1/28/21	1/29/21	1/30/21	1/31/21	2/1/21	2/2/21	2/3/21	2/4/21	2/5/21	2/6/21	2/7/21	2/8/21	2/9/21	2/10/21	2/11/21	2/12/21	2/13/21	2/14/21	2/15/21	2/16/21	2/17/21	2/18/21	2/19/21	2/20/21	2/21/21	2/22/21	2/23/21	2/24/21	2/25/21	2/26/21	2/27/21	2/28/21	3/1/21	3/2/21	3/3/21	3/4/21	3/5/21	3/6/21	3/7/21	3/8/21	3/9/21	3/10/21	3/11/21	3/12/21	3/13/21	3/14/21	3/15/21	3/16/21	3/17/21	3/18/21	3/19/21	3/20/21	3/21/21	3/22/21	3/23/21	3/24/21	3/25/21	3/26/21	3/27/21	3/28/21	3/29/21	3/30/21	3/31/21	4/1/21	4/2/21	4/3/21	4/4/21	4/5/21	4/6/21	4/7/21	4/8/21	4/9/21	4/10/21	4/11/21	4/12/21	4/13/21	4/14/21	4/15/21	4/16/21	4/17/21	4/18/21	4/19/21	4/20/21	4/21/21	4/22/21	4/23/21	4/24/21	4/25/21	4/26/21	4/27/21	4/28/21	4/29/21	4/30/21	5/1/21	5/2/21	5/3/21	5/4/21	5/5/21	5/6/21	5/7/21	5/8/21	5/9/21	5/10/21	5/11/21	5/12/21	5/13/21	5/14/21	5/15/21	5/16/21	5/17/21	5/18/21	5/19/21	5/20/21	5/21/21	5/22/21	5/23/21	5/24/21	5/25/21	5/26/21	5/27/21	5/28/21	5/29/21	5/30/21	5/31/21	6/1/21	6/2/21	6/3/21	6/4/21	6/5/21	6/6/21	6/7/21	6/8/21	6/9/21	6/10/21	6/11/21	6/12/21	6/13/21	6/14/21	6/15/21	6/16/21	6/17/21	6/18/21	6/19/21	6/20/21	6/21/21	6/22/21	6/23/21	6/24/21	6/25/21	6/26/21	6/27/21	6/28/21	6/29/21	6/30/21	7/1/21	7/2/21	7/3/21	7/4/21	7/5/21	7/6/21	7/7/21	7/8/21	7/9/21	7/10/21	7/11/21	7/12/21	7/13/21	7/14/21	7/15/21	7/16/21	7/17/21	7/18/21	7/19/21	7/20/21	7/21/21	7/22/21	7/23/21	7/24/21	7/25/21	7/26/21	7/27/21	7/28/21	7/29/21	7/30/21	7/31/21	8/1/21	8/2/21	8/3/21	8/4/21	8/5/21	8/6/21	8/7/21	8/8/21	8/9/21	8/10/21	8/11/21	8/12/21	8/13/21	8/14/21	8/15/21	8/16/21	8/17/21	8/18/21	8/19/21	8/20/21	8/21/21	8/22/21	8/23/21	8/24/21	8/25/21	8/26/21	8/27/21	8/28/21	8/29/21	8/30/21	8/31/21	9/1/21	9/2/21	9/3/21	9/4/21	9/5/21	9/6/21	9/7/21	9/8/21	9/9/21	9/10/21	9/11/21	9/12/21	9/13/21	9/14/21	9/15/21	9/16/21	9/17/21	9/18/21	9/19/21	9/20/21	9/21/21	9/22/21	9/23/21	9/24/21	9/25/21	9/26/21	9/27/21	9/28/21	9/29/21	9/30/21	10/1/21	10/2/21	10/3/21	10/4/21	10/5/21	10/6/21	10/7/21	10/8/21	10/9/21	10/10/21	10/11/21	10/12/21	10/13/21	10/14/21	10/15/21	10/16/21	10/17/21	10/18/21	10/19/21	10/20/21	10/21/21	10/22/21	10/23/21	10/24/21	10/25/21	10/26/21	10/27/21	10/28/21	10/29/21	10/30/21	10/31/21	11/1/21	11/2/21	11/3/21	11/4/21	11/5/21	11/6/21	11/7/21	11/8/21	11/9/21	11/10/21	11/11/21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3	NaN	Andorra	42.50630	1.521800	0	0	0	0	0	0	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	2	39	39	53	75	88	113	133	164	188	224	267	308	334	370	376	390	428	439	466	501	525	545	564	583	601	601	638	646	659	673	673	696	704	713	717	717	723	723	731	738	738	743	743	743	745	745	747	748	750	751	751	752	752	754	755	755	758	760	761	761	761	761	761	761	762	762	762	762	762	763	763	763	763	764	764	764	765	844	851	852	852	852	852	852	852	852	852	853	853	853	853	854	854	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	855	858	861	862	877	880	880	880	884	884	889	889	897	897	897	907	907	918	922	925	925	925	937	939	939	944	955	955	955	963	963	977	981	989	989	989	1005	1005	1024	1024	1045	1045	1045	1060	1060	1098	1098	1124	1124	1124	1176	1184	1199	1199	1215	1215	1215	1261	1261	1301	1301	1344	1344	1344	1438	1438	1483	1483	1564	1564	1564	1681	1681	1753	1753	1836	1836	1836	1966	1966	2050	2050	2110	2110	2110	2370	2370	2568	2568	2696	2696	2696	2995	2995	3190	3190	3377	3377	3377	3623	3623	3811	3811	4038	4038	4038	4325	4410	4517	4567	4665	4756	4825	4888	4910	5045	5135	5135	5319	5383	5437	5477	5567	5616	5725	5725	5872	5914	5951	6018	6066	6142	6207	6256	6304	6351	6428	6534	6610	6610	6712	6745	6790	6842	6904	6955	7005	7050	7084	7127	7162	7190	7236	7288	7338	7382	7382	7446	7466	7519	7560	7577	7602	7633	7669	7699	7756	7806	7821	7875	7919	7983	8049	8117	8166	8192	8249	8308	8348	8348	8489	8586	8586	8586	8682	8818	8868	8946	9038	9083	9083	9194	9308	9379	9416	9499	9549	9596	9638	9716	9779	9837	9885	9937	9972	10017	10070	10137	10172	10206	10251	10275	10312	10352	10391	10427	10463	10503	10538	10555	10583	10610	10645	10672	10699	10712	10739	10775	10799	10822	10849	10866	10889	10908	10948	10976	10998	11019	11042	11069	11089	11130	11130	11199	11228	11266	11289	11319	11360	11393	11431	11481	11517	11545	11591	11638	11687	11732	11809	11850	11888	11944	12010	12053	12115	12174	12231	12286	12328	12363	12409	12456	12497	12545	12581	12614	12641	12641	12712	12771	12805	12805	12874	12917	12942	13007	13024	13060	13083	13121	13148	13198	13232	13232	13282	13295	13316	13340	13363	13390	13406	13423	13429	13447	13470	13470	13510	13510	13510	13555	13569	13569	13569	13569	13569	13569	13569	13664	13671	13682	13693	13693	13693	13727	13729	13744	13752	13758	13758	13758	13777	13781	13791	13805	13813	13813	13813	13826	13828	13836	13839	13842	13842	13842	13864	13864	13873	13877	13882	13882	13882	13882	13900	13911	13918	13918	13918	13918	13918	13991	14021	14050	14075	14075	14075	14155	14167	14167	14239	14273	14273	14273	14359	14379	14379	14464	14498	14498	14498	14577	14586	14586	14655	14678	14678	14678	14747	14766	14797	14809	14836	14836	14836	14836	14873	14891	14908	14924	14924	14924	14954	14960	14976	14981	14988	14988	14988	15002	15003	15014	15016	15025	15025	15025	15032	15033	15046	15052	15055	15055	15055	15069	15070	15070	15078	15083	15083	15083	15096	15099	15108	15113	15124	15124	15124	15140	15140	15153	15156	15167	15167	15167	15189	15192	15209	15222	15222	15222	15222	15267	15271	15284	15288	15291	15291	15291	15307	15307	15314	15326	15338	15338	15338	15367	15369	15382	15382	15404	15404	15404	15425	15425	15462	15505	15516	15516	15516	15516	15516	15572	15618	15618	15618	15618	15705	15717	15744	15744	15819	15819	15819	15907	15929	15972	16035	16086	16086	16086	16299	16342	16426	16566	16712	16712	16712	16712	17115	17426	17658	18010	18010	18010	18631	18815	18815	19272	19440	19440	19440	19440	20136	20136	20549	20549	20549	20549	21062	21062	21372	21571	21730	21730	21730	22332	22540	22823	23122	23740	23740	23740	24502	24802	25289	25289	26408	26408	26408	27983	28542	28899	28899	29888	29888	29888	29888	29888	29888	32201	33025	33025	33025	33025	34701	35028	35028	35556	35556	35556	35958	35958	36315	36470	36599	36599	36599	36808	36808	36989	37074	37140	37140	37140	37277	37361	37452	37522	37589	37589	37589	37589	37820	37901	37958	37999	37999	37999	37999	38165	38249	38342	38434	38434	38434	38620	38710	38794	38794	38794	38794	38794	38794	38794	38794	39234	39234	39234	39234	39234	39234	39713	39713	39713	39713	39713	39713	39713	40024	40024	40024	40024	40024	40024	40024	40024	40328	40328	40328	40328	40328	40328	40709	40709	40709	40709	40709	40709	40709	41013	41013	41013	41013	41013	41013	41013	41013	41349	41349	41349	41349	41349	41349	41717	41717	41717	41717	41717	41717	41717	41717	42156	42156	42156	42156	42156	42156	42572	42572	42572	42572	42572	42572	42572	42894	42894	42894	42894	42894	42894	42894	42894	42894	43067	43067	43067	43067	43067	43224	43224	43224	43224	43224	43224	43224	43449	43449	43449	43449	43449	43449	43449	43774	43774	43774	43774	43774	43774	43774	43774	43774	44177	44177	44177	44177	44177	44671	44671	44671	44671	44671	44671	44671	44671	44671	44671	44671	44671	45061	45061	45061	45326	45326	45326	45326	45326	45326	45326	45508	45508	45508	45508	45508	45508	45793	45793	45793	45793	45793	45793	45793	45899	45899	45899	45899	45899	45899	45899	45975	45975	45975	45975	45975	45975	45975	46027	46027	46027	46027	46027	46027	46027	46027	46027	46027	4602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4	NaN	Angola	-11.20270	17.873900	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	2	3	3	3	4	4	5	7	7	7	8	8	8	10	14	16	17	19	19	19	19	19	19	19	19	19	19	24	24	24	24	25	25	25	25	26	27	27	27	27	30	35	35	35	36	36	36	43	43	45	45	45	45	48	48	48	48	50	52	52	58	60	61	69	70	70	71	74	81	84	86	86	86	86	86	86	88	91	92	96	113	118	130	138	140	142	148	155	166	172	176	183	186	189	197	212	212	259	267	276	284	291	315	328	346	346	346	386	386	396	458	462	506	525	541	576	607	638	687	705	749	779	812	851	880	916	932	950	1000	1078	1109	1148	1164	1199	1280	1344	1395	1483	1538	1572	1672	1679	1735	1762	1815	1852	1879	1906	1935	1966	2015	2044	2068	2134	2171	2222	2283	2332	2415	2471	2551	2624	2654	2729	2777	2805	2876	2935	2965	2981	3033	3092	3217	3279	3335	3388	3439	3569	3675	3789	3848	3901	3991	4117	4236	4363	4475	4590	4672	4718	4797	4905	4972	5114	5211	5370	5402	5530	5725	5725	5958	6031	6246	6366	6488	6680	6846	7096	7222	7462	7622	7829	8049	8338	8582	8829	9026	9381	9644	9871	10074	10269	10558	10805	11035	11228	11577	11813	12102	12223	12335	12433	12680	12816	12953	13053	13228	13374	13451	13615	13818	13922	14134	14267	14413	14493	14634	14742	14821	14920	15008	15087	15103	15139	15251	15319	15361	15493	15536	15591	15648	15729	15804	15925	16061	16161	16188	16277	16362	16407	16484	16562	16626	16644	16686	16802	16931	17029	17099	17149	17240	17296	17371	17433	17553	17568	17608	17642	17684	17756	17864	17974	18066	18156	18193	18254	18343	18425	18613	18679	18765	18875	18926	19011	19093	19177	19269	19367	19399	19476	19553	19580	19672	19723	19782	19796	19829	19900	19937	19996	20030	20062	20086	20112	20163	20210	20261	20294	20329	20366	20381	20389	20400	20452	20478	20499	20519	20548	20584	20640	20695	20759	20782	20807	20854	20882	20923	20981	21026	21055	21086	21108	21114	21161	21205	21265	21323	21380	21407	21446	21489	21558	21642	21696	21733	21757	21774	21836	21914	21961	22031	22063	22132	22182	22311	22399	22467	22579	22631	22717	22885	23010	23108	23242	23331	23457	23549	23697	23841	23951	24122	24300	24389	24518	24661	24883	25051	25279	25492	25609	25710	25942	26168	26431	26652	26815	26993	27133	27284	27529	27921	28201	28477	28740	28875	29146	29405	29695	30030	30354	30637	30787	31045	31438	31661	31909	32149	32441	32623	32933	33338	33607	33944	34180	34366	34551	34752	34960	35140	35307	35594	35772	35854	36004	36115	36325	36455	36600	36705	36790	36921	37094	37289	37467	37604	37678	37748	37874	38002	38091	38371	38528	38556	38613	38682	38849	38965	39089	39172	39230	39300	39375	39491	39593	39791	39881	39958	40055	40138	40327	40530	40631	40707	40805	40906	41061	41227	41405	41629	41736	41780	41879	42110	42288	42486	42646	42777	42815	42970	43070	43158	43269	43487	43592	43662	43747	43890	43998	44174	44328	44534	44617	44739	44972	45175	45325	45583	45817	45945	46076	46340	46539	46726	46929	47079	47168	47331	47544	47781	48004	48261	48475	48656	48790	49114	49349	49628	49943	50348	50446	50738	51047	51407	51827	52208	52307	52307	52644	52968	53387	53840	54280	54795	55121	55583	56040	56583	56583	58076	58603	58943	58943	59895	60448	60803	61023	61245	61378	61580	61794	62143	62385	62606	62789	62842	63012	63197	63340	63567	63691	63775	63861	63930	64033	64126	64226	64301	64374	64433	64458	64487	64533	64583	64612	64654	64674	64724	64762	64815	64857	64875	64899	64913	64913	64940	64968	64985	64997	65011	65024	65033	65061	65080	65105	65130	65139	65144	65155	65168	65183	65208	65223	65244	65259	65259	65301	65332	65346	65371	65397	65404	65404	65431	65565	65648	65760	65868	65938	66086	66566	67199	68362	70221	71142	71752	71752	76787	78475	79871	81593	82398	82920	83764	84666	86636	87625	88775	89251	89718	90316	91148	91907	92581	93302	93524	93694	93974	94275	94779	95220	95676	95902	96582	97263	97594	97812	97901	98029	98057	98076	98116	98226	98267	98319	98340	98351	98364	98409	98424	98453	98474	98501	98514	98514	98514	98555	98568	98585	98605	98617	98638	98658	98671	98698	98701	98701	98701	98701	98741	98746	98746	98746	98796	98796	98806	98806	98829	98855	98855	98855	98909	98927	98931	98956	98985	99003	99003	99003	99003	99010	99058	99058	99081	99102	99106	99115	99115	99138	99138	99169	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99194	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99287	99433	99527	99527	99527	99527	99527	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	99761	101320	101320	101320	101320	101320	101320	101320	101320	101320	101320	101320	101320	101320	101320	101320	101320	101600	101901	101901	101901	102209	102209	102209	102209	102301	102301	102301	102301	102301	102301	102301	102301	102301	102301	102301	102301	102301	102301	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	102636	1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0	NaN	Afghanistan	33.93911	67.709953	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	2	2	2	4	4	4	4	4	5	5	7	7	11	14	15	15	15	18	19	22	25	29	30	30	30	33	36	36	40	40	43	49	50	60	60	60	64	72	72	72	72	95	104	105	105	119	120	127	127	136	153	168	169	173	177	187	193	205	215	222	223	224	230	239	250	252	254	269	274	298	303	313	331	361	373	380	409	430	450	455	475	480	488	508	550	552	552	585	602	622	643	679	684	707	733	737	739	778	811	823	830	868	891	924	940	941	975	979	1014	1016	1049	1098	1117	1151	1151	1185	1187	1188	1194	1215	1229	1250	1263	1273	1274	1275	1275	1275	1287	1287	1287	1292	1298	1302	1302	1311	1316	1316	1348	1358	1367	1367	1374	1379	1379	1379	1379	1387	1389	1389	1389	1391	1401	1405	1405	1406	1406	1406	1406	1410	1413	1413	1413	1413	1416	1419	1422	1424	1424	1424	1424	1424	1429	1430	1440	1440	1441	1441	1445	1448	1449	1450	1455	1455	1457	1457	1460	1462	1462	1462	1462	1466	1466	1470	1471	1473	1474	1476	1477	1481	1483	1484	1485	1485	1489	1492	1496	1501	1503	1503	1503	1505	1507	1511	1514	1518	1523	1529	1532	1533	1536	1536	1541	1544	1548	1554	1554	1556	1562	1574	1577	1581	1591	1595	1605	1617	1626	1638	1645	1650	1661	1675	1687	1695	1712	1725	1737	1740	1752	1763	1774	1795	1822	1841	1847	1865	1875	1902	1908	1921	1939	1949	1960	1971	1975	2001	2017	2032	2037	2054	2074	2089	2105	2126	2135	2148	2158	2170	2182	2189	2189	2201	2211	2221	2230	2237	2244	2253	2257	2264	2277	2288	2301	2308	2314	2324	2336	2339	2343	2346	2354	2363	2370	2373	2378	2385	2389	2389	2397	2399	2400	2400	2404	2405	2406	2407	2407	2408	2410	2413	2414	2418	2419	2424	2427	2427	2427	2428	2428	2430	2430	2430	2432	2433	2435	2436	2438	2442	2443	2443	2444	2446	2446	2446	2449	2449	2449	2451	2451	2451	2451	2454	2454	2457	2459	2460	2460	2462	2462	2462	2463	2464	2466	2466	2467	2467	2469	2470	2472	2476	2484	2489	2495	2496	2497	2508	2512	2512	2516	2521	2521	2521	2529	2529	2532	2533	2535	2539	2539	2546	2549	2557	2561	2565	2572	2582	2592	2598	2611	2618	2625	2631	2637	2642	2648	2654	2664	2673	2683	2686	2698	2710	2713	2721	2730	2733	2742	2745	2751	2762	2772	2782	2792	2802	2812	2836	2855	2869	2881	2899	2919	2944	2973	3007	3034	3068	3104	3145	3187	3251	3305	3356	3412	3449	3527	3612	3683	3683	3842	3934	4030	4122	4215	4293	4366	4452	4519	4594	4650	4730	4794	4871	4962	5048	5107	5199	5283	5360	5415	5477	5561	5638	5724	5791	5849	5923	5983	6072	6098	6147	6213	6266	6293	6325	6357	6393	6425	6477	6515	6577	6615	6677	6708	6737	6774	6804	6836	6864	6879	6897	6908	6936	6961	6978	6988	7000	7010	7021	7025	7031	7043	7047	7054	7065	7070	7076	7083	7090	7093	7101	7103	7109	7116	7118	7123	7127	7127	7128	7132	7141	7144	7151	7157	7164	7167	7167	7169	7171	7174	7183	7186	7186	7186	7199	7199	7199	7199	7199	7199	7199	7200	7201	7204	7204	7206	7206	7206	7212	7214	7220	7221	7221	7221	7225	7228	7230	7234	7238	7238	7238	7243	7246	7247	7247	7249	7252	7253	7255	7260	7262	7266	7268	7269	7272	7280	7281	7281	7284	7284	7284	7284	7284	7288	7290	7291	7292	7292	7292	7293	7294	7295	7297	7297	7299	7301	7303	7303	7305	7306	7307	7307	7308	7308	7308	7308	7309	7310	7311	7312	7312	7316	7317	7319	7321	7324	7325	7328	7328	7329	7331	7332	7332	7333	7335	7335	7335	7341	7346	7348	7349	7354	7354	7355	7356	7356	7356	7356	7361	7364	7365	7367	7367	7368	7369	7373	7373	7374	7376	7376	7376	7378	7379	7381	7383	7386	7386	7390	7390	7393	7393	7397	7401	7403	7403	7405	7408	7414	7417	7418	7420	7420	7425	7432	7442	7454	7465	7477	7478	7488	7494	7501	7504	7513	7524	7526	7534	7539	7549	7569	7574	7578	7579	7585	7593	7598	7609	7617	7619	7619	7622	7623	7626	7630	7636	7639	7640	7641	7643	7645	7646	7651	7651	7651	7652	7654	7654	7656	7657	7657	7657	7657	7662	7663	7665	7667	7670	7670	7671	7671	7671	7671	7671	7671	7671	7671	7671	7675	7676	7676	7676	7676	7676	7678	7679	7680	7680	7680	7680	7681	7682	7683	7683	7683	7683	7683	7683	7683	7683	7683	7683	7684	7684	7684	7684	7685	7685	7686	7686	7686	7687	7690	7691	7691	7691	7695	7695	7697	7698	7698	7698	7699	7699	7699	7701	7701	7701	7705	7707	7708	7708	7708	7708	7709	7709	7709	7709	7709	7709	7709	7710	7710	7710	7713	7713	7713	7713	7714	7715	7715	7715	7717	7717	7717	7720	7722	7722	7723	7723	7723	7724	7725	7725	7725	7727	7728	7728	7728	7728	7728	7728	7728	7729	7730	7731	7733	7736	7737	7738	7738	7738	7738	7738	7742	7743	7743	7743	7745	7748	7751	7751	7752	7752	7752	7752	7752	7753	7753	7753	7755	7755	7758	7758	7759	7759	7759	7759	7759	7759	7762	7767	7768	7769	7771	7771	7771	7777	7777	7777	7777	7778	7778	7780	7782	7783	7783	7785	7786	7786	7787	7787	7789	7791	7792	7792	7794	7794	7795	7796	7796	7796	7796	7796	7796	7796	7798	7798	7799	7799	7800	7800	7801	7803	7803	7804	7804	7804	7804	7806	7807	7807	7807	7809	7809	7811
1	NaN	Albania	41.15330	20.168300	1	1	1	1	1	1	1	2	2	2	2	2	4	5	5	6	8	10	10	11	15	15	16	17	20	20	21	22	22	23	23	23	23	23	24	25	26	26	26	26	26	26	27	27	27	27	28	28	30	30	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	31	32	32	33	33	33	33	33	33	33	33	33	33	33	34	34	34	34	34	35	36	36	36	36	37	38	39	42	43	44	44	45	47	49	51	53	55	58	62	65	69	72	74	76	79	81	83	83	85	89	93	95	97	101	104	107	111	112	113	117	120	123	128	134	138	144	148	150	154	157	161	166	172	176	182	188	189	193	199	200	205	208	213	219	225	228	230	232	234	238	240	245	250	254	259	263	266	271	275	280	284	290	296	301	306	312	316	319	321	322	324	327	330	334	338	340	343	347	353	358	362	364	367	370	370	373	375	377	380	384	387	388	389	392	396	400	403	407	411	413	416	420	424	429	434	439	443	448	451	454	458	462	465	469	473	477	480	487	493	499	502	509	518	527	532	536	543	549	557	559	571	579	590	598	605	612	623	631	637	646	657	672	685	699	716	735	743	753	771	787	798	810	822	839	852	870	889	905	922	936	951	965	977	989	1003	1016	1028	1040	1055	1066	1074	1088	1098	1111	1117	1125	1134	1143	1153	1164	1170	1174	1181	1181	1190	1193	1199	1210	1217	1223	1230	1233	1241	1247	1252	1256	1261	1265	1270	1277	1281	1287	1291	1296	1303	1310	1315	1324	1332	1339	1350	1358	1369	1380	1393	1398	1404	1418	1433	1446	1460	1472	1488	1503	1517	1531	1543	1555	1567	1582	1600	1617	1636	1653	1666	1681	1696	1715	1736	1756	1775	1796	1816	1835	1856	1876	1897	1918	1939	1956	1969	1986	2002	2018	2030	2045	2060	2077	2092	2106	2122	2133	2137	2145	2156	2171	2184	2192	2204	2210	2216	2227	2235	2241	2247	2256	2265	2274	2283	2291	2297	2304	2310	2317	2321	2326	2331	2335	2337	2340	2342	2347	2353	2358	2364	2367	2372	2378	2379	2383	2386	2389	2394	2396	2397	2399	2402	2403	2406	2408	2411	2412	2416	2420	2423	2426	2427	2429	2432	2435	2436	2438	2440	2441	2442	2444	2445	2447	2447	2447	2448	2449	2450	2451	2451	2451	2451	2451	2451	2451	2452	2452	2452	2452	2453	2453	2453	2453	2454	2454	2454	2454	2454	2454	2454	2455	2455	2455	2455	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2456	2457	2457	2457	2457	2457	2457	2457	2457	2457	2458	2459	2459	2460	2460	2460	2460	2461	2463	2464	2466	2468	2471	2473	2475	2477	2478	2478	2480	2483	2486	2487	2490	2492	2495	2498	2501	2505	2508	2512	2515	2519	2523	2528	2531	2535	2539	2543	2548	2553	2557	2563	2569	2574	2580	2587	2594	2601	2609	2619	2629	2640	2653	2668	2685	2698	2705	2710	2713	2713	2725	2734	2746	2753	2759	2768	2777	2783	2788	2797	2807	2810	2820	2829	2841	2849	2855	2863	2870	2874	2880	2888	2893	2902	2909	2916	2924	2931	2937	2940	2944	2948	2948	2955	2966	2970	2975	2978	2983	2986	2990	2997	3004	3014	3022	3029	3035	3035	3049	3053	3063	3068	3077	3085	3089	3092	3096	3101	3104	3108	3109	3110	3115	3122	3126	3128	3130	3132	3134	3140	3144	3152	3156	3158	3161	3166	3172	3178	3180	3181	3187	3189	3194	3194	3207	3212	3212	3217	3217	3220	3220	3224	3224	3228	3233	3233	3240	3241	3247	3253	3255	3262	3265	3269	3271	3277	3283	3286	3292	3297	3305	3305	3312	3317	3323	3329	3329	3334	3346	3346	3362	3362	3371	3371	3380	3387	3393	3399	3402	3402	3407	3410	3414	3420	3423	3430	3432	3433	3438	3445	3451	3453	3457	3458	3458	3464	3469	3472	3474	3474	3478	3478	3482	3483	3483	3483	3484	3485	3485	3485	3485	3486	3487	3487	3487	3487	3487	3487	3489	3489	3489	3490	3491	3491	3491	3492	3492	3492	3492	3492	3492	3492	3492	3492	3492	3492	3492	3493	3493	3494	3494	3495	3495	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3496	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3497	3498	3499	3500	3501	3501	3502	3502	3502	3506	3508	3510	3512	3514	3514	3516	3517	3517	3517	3517	3517	3518	3520	3521	3521	3523	3525	3527	3529	3532	3535	3538	3541	3543	3545	3548	3550	3551	3554	3557	3560	3563	3566	3566	3567	3568	3569	3570	3571	3571	3573	3574	3574	3575	3576	3576	3576	3577	3578	3579	3580	3581	3581	3581	3582	3582	3583	3583	3583	3583	3583	3583	3584	3584	3584	3584	3584	3585	3586	3586	3586	3586	3586	3586	3588	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3589	3590	3591	3591	3591	3591
2	NaN	Algeria	28.03390	1.659600	0	1	2	3	4	4	4	7	9	11	15	17	17	19	21	25	26	29	31	35	44	58	86	105	130	152	173	193	205	235	256	275	293	313	326	336	348	364	367	375	384	392	402	407	415	419	425	432	437	444	450	453	459	463	465	470	476	483	488	494	502	507	515	522	529	536	542	548	555	561	568	575	582	592	600	609	617	623	630	638	646	653	661	667	673	681	690	698	707	715	724	732	741	751	760	767	777	788	799	811	825	837	845	852	861	869	878	885	892	897	905	912	920	928	937	946	952	959	968	978	988	996	1004	1011	1018	1028	1040	1052	1057	1068	1078	1087	1100	1111	1124	1136	1146	1155	1163	1174	1186	1200	1210	1223	1231	1239	1248	1261	1273	1282	1293	1302	1312	1322	1333	1341	1351	1360	1370	1379	1391	1402	1411	1418	1424	1435	1446	1456	1465	1475	1483	1491	1501	1510	1518	1523	1529	1539	1549	1556	1562	1571	1581	1591	1599	1605	1612	1620	1632	1645	1654	1659	1665	1672	1679	1689	1698	1703	1707	1711	1714	1719	1726	1736	1741	1749	1756	1760	1768	1768	1771	1783	1789	1795	1801	1809	1818	1827	1827	1841	1846	1856	1865	1873	1880	1888	1897	1907	1914	1922	1931	1941	1949	1956	1964	1973	1980	1980	1999	2011	2024	2036	2048	2062	2077	2093	2111	2124	2139	2154	2168	2186	2206	2224	2236	2255	2272	2294	2309	2329	2352	2372	2393	2410	2431	2447	2464	2480	2492	2501	2516	2527	2539	2554	2564	2575	2584	2596	2609	2623	2631	2640	2647	2659	2666	2675	2687	2696	2705	2716	2722	2728	2737	2745	2751	2756	2762	2769	2772	2777	2782	2786	2792	2798	2803	2807	2812	2816	2819	2822	2827	2831	2836	2840	2843	2849	2853	2856	2861	2863	2866	2871	2877	2881	2884	2888	2891	2894	2898	2900	2904	2909	2909	2914	2918	2924	2926	2930	2932	2935	2939	2943	2945	2947	2950	2954	2958	2961	2964	2967	2970	2973	2977	2979	2983	2987	2991	2996	3002	3007	3010	3013	3018	3022	3026	3028	3031	3034	3036	3040	3045	3048	3051	3053	3055	3057	3061	3066	3069	3071	3074	3077	3080	3084	3089	3093	3096	3099	3102	3105	3108	3112	3116	3119	3123	3126	3130	3134	3137	3141	3144	3148	3152	3155	3160	3165	3172	3181	3190	3198	3207	3217	3225	3234	3244	3253	3261	3270	3280	3289	3299	3307	3315	3321	3328	3335	3343	3350	3355	3360	3366	3374	3381	3388	3395	3401	3405	3411	3418	3426	3433	3440	3448	3455	3460	3465	3472	3480	3490	3497	3504	3510	3518	3527	3537	3544	3552	3560	3565	3571	3579	3588	3598	3605	3615	3624	3631	3641	3650	3660	3669	3678	3685	3693	3699	3708	3716	3726	3735	3745	3755	3765	3775	3786	3798	3811	3824	3836	3851	3867	3882	3895	3910	3922	3938	3956	3979	3994	4008	4026	4042	4063	4087	4112	4161	4189	4219	4254	4291	4329	4370	4404	4441	4487	4520	4550	4578	4618	4654	4695	4730	4766	4794	4830	4867	4898	4929	4957	4984	5004	5034	5063	5096	5121	5148	5179	5209	5240	5269	5302	5339	5373	5399	5420	5445	5471	5489	5519	5539	5558	5578	5596	5614	5630	5651	5670	5681	5694	5709	5725	5739	5748	5758	5767	5777	5786	5797	5805	5812	5815	5819	5822	5826	5831	5838	5843	5846	5850	5853	5855	5859	5862	5864	5867	5870	5872	5873	5875	5878	5881	5883	5886	5890	5894	5899	5904	5907	5913	5918	5920	5924	5927	5931	5936	5939	5941	5945	5950	5954	5960	5966	5971	5977	5984	5991	5997	6005	6009	6015	6017	6021	6026	6030	6035	6041	6046	6052	6058	6064	6071	6076	6083	6089	6096	6103	6111	6114	6122	6126	6132	6137	6145	6151	6155	6165	6171	6175	6180	6184	6190	6198	6205	6213	6222	6229	6238	6246	6254	6263	6271	6276	6284	6291	6298	6303	6310	6318	6325	6330	6339	6349	6363	6372	6383	6393	6404	6412	6423	6435	6443	6453	6468	6481	6495	6508	6516	6526	6539	6545	6555	6566	6579	6593	6604	6618	6631	6640	6646	6654	6667	6678	6690	6703	6715	6729	6744	6753	6762	6772	6780	6787	6797	6805	6812	6816	6820	6823	6828	6831	6835	6840	6843	6848	6852	6853	6855	6857	6858	6860	6861	6861	6862	6864	6866	6868	6869	6870	6871	6871	6871	6872	6873	6873	6873	6873	6873	6873	6873	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6874	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6875	6876	6876	6876	6876	6876	6876	6876	6876	6876	6876	6876	6877	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6878	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6879	6881	6881	6881	6881	6881	6881	6881	6881	6881	6881
3	NaN	Andorra	42.50630	1.521800	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	3	3	3	6	8	12	14	15	16	17	18	21	22	23	25	26	26	29	29	31	33	33	35	35	36	37	37	37	37	40	40	40	40	41	42	42	43	44	45	45	46	46	47	47	48	48	48	48	49	49	49	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	51	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	52	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	53	54	55	55	55	57	57	59	59	59	59	59	62	62	63	63	69	69	69	72	72	72	73	75	75	75	75	75	75	75	75	75	75	75	75	75	75	75	75	76	76	76	76	76	76	76	76	76	76	76	76	76	76	76	76	76	76	77	77	78	78	78	78	78	78	78	78	79	79	79	79	79	80	80	81	81	82	82	83	83	83	83	83	84	84	84	84	84	84	84	84	84	84	84	85	85	85	86	87	88	88	91	91	91	92	92	93	93	96	96	97	97	98	100	100	101	101	101	102	103	103	104	105	106	106	106	106	106	106	107	107	107	107	107	107	107	107	107	109	110	110	110	110	110	110	110	110	112	112	112	112	112	112	112	112	112	112	112	113	113	113	113	113	113	113	113	113	113	114	114	114	115	115	115	115	115	115	116	117	117	117	117	119	120	120	120	120	121	121	121	121	123	123	123	123	123	123	123	123	124	124	124	124	125	125	125	125	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	127	128	128	128	128	128	128	128	128	128	128	128	129	129	129	129	129	129	129	129	129	129	129	129	129	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	130	131	131	131	131	131	131	131	131	132	132	132	132	133	133	133	133	133	133	133	133	134	134	134	134	134	134	137	137	138	139	139	139	139	139	140	140	140	140	140	140	140	141	141	141	141	141	141	141	141	141	141	142	142	142	142	142	142	144	144	144	144	144	145	145	145	145	145	145	145	145	146	147	147	147	147	147	147	148	148	148	148	148	149	150	150	150	150	150	150	150	151	151	151	151	151	151	151	151	151	151	151	151	151	151	152	152	152	152	152	152	152	152	152	153	153	153	153	153	153	153	155	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	153	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	154	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155	155
4	NaN	Angola	-11.20270	17.873900	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	2	3	3	3	3	3	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	5	5	6	6	6	6	7	8	8	9	9	10	10	10	10	10	10	11	11	13	15	17	18	19	19	19	21	21	22	23	23	26	26	26	27	28	29	29	29	29	30	33	33	35	39	40	41	47	48	51	52	54	55	58	59	62	64	67	70	75	78	80	80	80	86	86	88	88	90	92	93	94	94	96	100	102	103	105	106	107	107	108	109	112	113	115	117	117	120	124	126	130	131	132	134	136	139	143	144	147	147	152	154	155	159	162	167	171	174	176	179	183	185	189	193	195	199	211	211	208	212	218	218	219	222	227	228	234	241	247	248	251	255	260	265	267	268	270	271	275	275	279	284	286	289	291	296	299	300	303	307	308	308	312	315	317	322	322	324	328	332	333	334	336	337	337	338	340	341	342	345	346	348	350	351	352	353	354	354	354	355	358	362	365	366	371	372	372	379	382	384	386	387	390	393	393	393	396	399	399	403	403	405	405	405	407	408	408	410	413	413	415	416	416	420	422	424	425	428	431	436	439	442	444	448	452	457	459	461	462	462	464	464	464	466	466	468	470	473	474	475	475	475	478	487	487	490	491	492	493	494	496	498	498	498	499	499	500	501	502	504	506	508	508	510	510	511	511	512	514	515	516	516	517	519	520	521	521	522	522	522	524	526	527	530	530	532	532	532	533	533	534	536	537	538	538	540	542	543	547	547	549	549	550	553	554	554	557	557	560	561	561	563	565	570	572	574	577	579	583	587	591	594	596	600	602	603	609	618	622	628	630	633	636	639	645	649	651	655	659	677	685	696	704	709	715	725	731	735	742	745	749	757	764	766	772	780	784	788	794	797	800	803	811	815	819	825	831	836	842	847	851	853	856	859	868	875	878	881	883	887	889	891	894	900	903	906	910	913	915	920	925	925	928	929	935	939	941	946	951	952	954	957	969	970	973	977	981	982	984	991	994	1000	1003	1008	1011	1016	1018	1022	1026	1032	1042	1044	1049	1053	1057	1063	1070	1082	1086	1100	1103	1118	1125	1133	1138	1140	1153	1163	1166	1176	1182	1186	1192	1201	1210	1217	1227	1235	1248	1258	1270	1282	1299	1309	1313	1322	1327	1339	1345	1358	1360	1371	1378	1388	1388	1409	1414	1434	1460	1471	1487	1501	1513	1526	1537	1537	1567	1574	1577	1577	1587	1598	1603	1613	1618	1622	1629	1642	1650	1653	1660	1662	1664	1670	1678	1682	1685	1693	1695	1697	1701	1702	1703	1705	1707	1708	1710	1713	1713	1716	1718	1719	1719	1720	1721	1723	1723	1725	1726	1727	1727	1727	1729	1729	1729	1729	1730	1730	1730	1730	1731	1732	1733	1733	1733	1733	1733	1735	1735	1735	1735	1735	1735	1735	1735	1736	1737	1737	1737	1737	1737	1737	1737	1738	1738	1738	1738	1738	1741	1743	1746	1746	1749	1749	1756	1760	1764	1770	1772	1772	1775	1778	1789	1799	1809	1819	1826	1832	1840	1842	1847	1852	1857	1863	1866	1870	1877	1881	1884	1886	1888	1888	1891	1892	1893	1893	1894	1895	1895	1895	1895	1896	1896	1896	1896	1896	1896	1896	1897	1898	1898	1898	1898	1899	1899	1899	1899	1899	1899	1899	1899	1899	1899	1899	1899	1899	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1900	1909	1909	1909	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1912	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917	1917

	Province/State	Country/Region	Lat	Long	3/12/20	3/13/20	3/14/20	3/15/20	3/16/20	3/17/20	3/18/20	3/19/20	3/20/20	3/21/20	3/22/20	3/23/20	3/24/20	3/25/20	3/26/20	3/27/20	3/28/20	3/29/20	3/30/20	3/31/20	4/1/20	4/2/20	4/3/20	4/4/20	4/5/20	4/6/20	4/7/20	4/8/20	4/9/20	4/10/20	4/11/20	4/12/20	4/13/20	4/14/20	4/15/20	4/16/20	4/17/20	4/18/20	4/19/20	4/20/20	4/21/20	4/22/20	4/23/20	4/24/20	4/25/20	4/26/20	4/27/20	4/28/20	4/29/20	4/30/20	5/1/20	5/2/20	5/3/20	5/4/20	5/5/20	5/6/20	5/7/20	5/8/20	5/9/20	5/10/20	5/11/20	5/12/20	5/13/20	5/14/20	5/15/20	5/16/20	5/17/20	5/18/20	5/19/20	5/20/20	5/21/20	5/22/20	5/23/20	5/24/20	5/25/20	5/26/20	5/27/20	5/28/20	5/29/20	5/30/20	5/31/20	6/1/20	6/2/20	6/3/20	6/4/20	6/5/20	6/6/20	6/7/20	6/8/20	6/9/20	6/10/20	6/11/20	6/12/20	6/13/20	6/14/20	6/15/20	6/16/20	6/17/20	6/18/20	6/19/20	6/20/20	6/21/20	6/22/20	6/23/20	6/24/20	6/25/20	6/26/20	6/27/20	6/28/20	6/29/20	6/30/20	7/1/20	7/2/20	7/3/20	7/4/20	7/5/20	7/6/20	7/7/20	7/8/20	7/9/20	7/10/20	7/11/20	7/12/20	7/13/20	7/14/20	7/15/20	7/16/20	7/17/20	7/18/20	7/19/20	7/20/20	7/21/20	7/22/20	7/23/20	7/24/20	7/25/20	7/26/20	7/27/20	7/28/20	7/29/20	7/30/20	7/31/20	8/1/20	8/2/20	8/3/20	8/4/20	8/5/20	8/6/20	8/7/20	8/8/20	8/9/20	8/10/20	8/11/20	8/12/20	8/13/20	8/14/20	8/15/20	8/16/20	8/17/20	8/18/20	8/19/20	8/20/20	8/21/20	8/22/20	8/23/20	8/24/20	8/25/20	8/26/20	8/27/20	8/28/20	8/29/20	8/30/20	8/31/20	9/1/20	9/2/20	9/3/20	9/4/20	9/5/20	9/6/20	9/7/20	9/8/20	9/9/20	9/10/20	9/11/20	9/12/20	9/13/20	9/14/20	9/15/20	9/16/20	9/17/20	9/18/20	9/19/20	9/20/20	9/21/20	9/22/20	9/23/20	9/24/20	9/25/20	9/26/20	9/27/20	9/28/20	9/29/20	9/30/20	10/1/20	10/2/20	10/3/20	10/4/20	10/5/20	10/6/20	10/7/20	10/8/20	10/9/20	10/10/20	10/11/20	10/12/20	10/13/20	10/14/20	10/15/20	10/16/20	10/17/20	10/18/20	10/19/20	10/20/20	10/21/20	10/22/20	10/23/20	10/24/20	10/25/20	10/26/20	10/27/20	10/28/20	10/29/20	10/30/20	10/31/20	11/1/20	11/2/20	11/3/20	11/4/20	11/5/20	11/6/20	11/7/20	11/8/20	11/9/20	11/10/20	11/11/20	11/12/20	11/13/20	11/14/20	11/15/20	11/16/20	11/17/20	11/18/20	11/19/20	11/20/20	11/21/20	11/22/20	11/23/20	11/24/20	11/25/20	11/26/20	11/27/20	11/28/20	11/29/20	11/30/20	12/1/20	12/2/20	12/3/20	12/4/20	12/5/20	12/6/20	12/7/20	12/8/20	12/9/20	12/10/20	12/11/20	12/12/20	12/13/20	12/14/20	12/15/20	12/16/20	12/17/20	12/18/20	12/19/20	12/20/20	12/21/20	12/22/20	12/23/20	12/24/20	12/25/20	12/26/20	12/27/20	12/28/20	12/29/20	12/30/20	12/31/20	1/1/21	1/2/21	1/3/21	1/4/21	1/5/21	1/6/21	1/7/21	1/8/21	1/9/21	1/10/21	1/11/21	1/12/21	1/13/21	1/14/21	1/15/21	1/16/21	1/17/21	1/18/21	1/19/21	1/20/21	1/21/21	1/22/21	1/23/21	1/24/21	1/25/21	1/26/21	1/27/21	1/28/21	1/29/21	1/30/21	1/31/21	2/1/21	2/2/21	2/3/21	2/4/21	2/5/21	2/6/21	2/7/21	2/8/21	2/9/21	2/10/21	2/11/21	2/12/21	2/13/21	2/14/21	2/15/21	2/16/21	2/17/21	2/18/21	2/19/21	2/20/21	2/21/21	2/22/21	2/23/21	2/24/21	2/25/21	2/26/21	2/27/21	2/28/21	3/1/21	3/2/21	3/3/21	3/4/21	3/5/21	3/6/21	3/7/21	3/8/21	3/9/21	3/10/21	3/11/21	3/12/21	3/13/21	3/14/21	3/15/21	3/16/21	3/17/21	3/18/21	3/19/21	3/20/21	3/21/21	3/22/21	3/23/21	3/24/21	3/25/21	3/26/21	3/27/21	3/28/21	3/29/21	3/30/21	3/31/21	4/1/21	4/2/21	4/3/21	4/4/21	4/5/21	4/6/21	4/7/21	4/8/21	4/9/21	4/10/21	4/11/21	4/12/21	4/13/21	4/14/21	4/15/21	4/16/21	4/17/21	4/18/21	4/19/21	4/20/21	4/21/21	4/22/21	4/23/21	4/24/21	4/25/21	4/26/21	4/27/21	4/28/21	4/29/21	4/30/21	5/1/21	5/2/21	5/3/21	5/4/21	5/5/21	5/6/21	5/7/21	5/8/21	5/9/21	5/10/21	5/11/21	5/12/21	5/13/21	5/14/21	5/15/21	5/16/21	5/17/21	5/18/21	5/19/21	5/20/21	5/21/21	5/22/21	5/23/21	5/24/21	5/25/21	5/26/21	5/27/21	5/28/21	5/29/21	5/30/21	5/31/21	6/1/21	6/2/21	6/3/21	6/4/21	6/5/21	6/6/21	6/7/21	6/8/21	6/9/21	6/10/21	6/11/21	6/12/21	6/13/21	6/14/21	6/15/21	6/16/21	6/17/21	6/18/21	6/19/21	6/20/21	6/21/21	6/22/21	6/23/21	6/24/21	6/25/21	6/26/21	6/27/21	6/28/21	6/29/21	6/30/21	7/1/21	7/2/21	7/3/21	7/4/21	7/5/21	7/6/21	7/7/21	7/8/21	7/9/21	7/10/21	7/11/21	7/12/21	7/13/21	7/14/21	7/15/21	7/16/21	7/17/21	7/18/21	7/19/21	7/20/21	7/21/21	7/22/21	7/23/21	7/24/21	7/25/21	7/26/21	7/27/21	7/28/21	7/29/21	7/30/21	7/31/21	8/1/21	8/2/21	8/3/21	8/4/21
0	NaN	Afghanistan	33.93911	67.709953	0	0	0	0	1	1	1	1	1	1	1	1	1	2	2	2	2	2	2	5	5	10	10	10	15	18	18	29	32	32	32	32	32	40	43	54	99	112	131	135	150	166	179	188	188	207	220	228	252	260	310	331	345	397	421	458	468	472	502	558	558	610	648	691	745	745	778	801	850	930	938	996	1040	1075	1097	1128	1138	1209	1259	1303	1328	1428	1450	1522	1585	1762	1830	1875	2171	2651	3013	3326	3928	4201	4725	5164	5508	6158	7660	7962	8292	8764	8841	9260	9869	10174	10306	10674	12604	13934	14131	15651	16041	17331	19164	19366	20103	20179	20700	20847	20882	21135	21216	21254	21454	22456	22824	23151	23273	23634	23741	23741	23924	24550	24602	24793	25180	25198	25358	25389	25471	25509	25509	25510	25669	25669	25742	25840	25903	25960	25960	26228	26415	26694	26714	26714	27166	27166	27166	27166	27166	27681	28016	28016	28180	28360	28440	29042	29046	29059	29063	29089	29089	29231	29315	29390	29713	30082	30537	30557	30715	31048	31129	31154	31234	31638	32073	32098	32503	32505	32576	32576	32576	32576	32576	32610	32619	32619	32635	32642	32642	32746	32789	32842	32842	32842	32852	32879	32977	33045	33058	33058	33064	33114	33118	33308	33354	33447	33516	33561	33614	33760	33790	33824	33831	34010	34023	34129	34150	34217	34237	34239	34258	34321	34326	34342	34355	34362	34440	34440	34446	34458	34721	34954	34967	35024	35036	35067	35092	35137	35160	35295	35350	35370	35422	35934	35976	36122	36145	36232	36295	36709	36716	36831	36946	37218	37260	37260	37393	37685	37879	37920	38032	38099	38141	38200	38250	38252	38336	38475	38505	38540	38613	39006	39508	39585	39692	40359	40444	40784	41096	41441	41543	41612	41727	41727	41727	41727	42530	42666	42666	43291	43440	43740	43948	44137	44608	44850	45298	45434	45465	45868	46359	46554	46759	46887	46912	46943	47298	47365	47459	47549	47583	47606	47609	47679	47723	47798	47982	47995	48018	48027	48041	48042	48109	48133	48279	48390	48392	48395	48433	48514	48626	48798	48803	48820	48834	48895	48967	49086	49281	49285	49288	49333	49344	49347	49359	49362	49362	49369	49378	49402	49409	49499	49499	49499	49471	49477	49481	49499	49536	49664	49681	49681	49737	49743	49752	49802	49937	49994	49994	50013	50666	51473	51550	51788	51798	51802	51885	51902	51928	51940	51956	51961	51962	51989	52005	52013	52022	52083	52105	52116	52168	52244	52272	52301	52348	52363	52392	52489	52520	52794	52974	53103	53206	53272	53391	53391	53694	53750	53961	54019	54040	54222	54382	54503	54534	54619	54634	54663	54686	55010	55118	55529	55687	55790	55889	56035	56295	56518	56711	56962	57119	57281	57450	57629	57741	57963	58070	58144	58265	58622	58998	59569	59871	60280	60598	60939	61410	61706	61820	62397	62698	63426	63875	64401	65071	65565	66102	66799	67183	67483	68288	69205	70016	71012	71924	72700	73635	74480	75314	76218	77280	78521	79446	80226	81077	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586	82586
1	NaN	Albania	41.15330	20.168300	0	0	0	0	0	0	0	0	0	2	2	2	10	17	17	31	31	33	44	52	67	76	89	99	104	116	131	154	165	182	197	217	232	248	251	277	283	302	314	327	345	356	385	394	403	410	422	431	455	470	488	519	531	543	570	595	605	620	627	650	654	682	688	694	705	714	715	727	742	758	771	777	783	789	795	803	812	823	851	857	872	877	891	898	898	910	925	938	945	960	980	1001	1034	1039	1044	1055	1064	1077	1086	1114	1126	1134	1159	1195	1217	1250	1298	1346	1384	1438	1459	1516	1559	1592	1637	1657	1702	1744	1791	1832	1875	1881	1946	2014	2062	2091	2137	2214	2264	2311	2352	2397	2463	2523	2608	2637	2682	2745	2789	2830	2883	2952	2961	3018	3031	3031	3123	3155	3227	3268	3342	3379	3480	3552	3616	3695	3746	3794	3816	3871	3928	3986	4096	4184	4332	4413	4530	4633	4791	4923	5020	5139	5214	5441	5582	5732	5882	5976	6106	6186	6239	6284	6346	6443	6494	6569	6615	6668	6733	6788	6831	6888	6940	6995	7042	7139	7239	7309	7397	7397	7629	7732	7847	8077	8342	8536	8675	8825	8965	9115	9215	9304	9406	9500	9585	9675	9762	9864	9957	10001	10071	10167	10225	10341	10395	10466	10548	10654	10705	10808	10893	11007	11097	11189	11246	11367	11473	11578	11696	11861	12002	12092	12203	12353	12493	12574	12667	12767	12889	13453	13804	14216	14565	15055	15469	15842	16230	16666	17031	17352	17755	18152	18481	18849	19384	19912	20484	20974	21286	21617	22180	22527	23072	23609	24136	24520	24820	24820	25876	26381	26898	27426	27831	28121	28752	29249	29799	30276	30790	31181	31565	32122	32700	33185	33634	33634	34353	34648	34996	35551	36102	36535	36971	37327	37648	37981	38421	38860	39246	39625	40090	40453	40870	41464	41969	42426	42895	43384	43890	44291	44880	45383	45906	46420	46927	47424	47922	48377	48958	49543	50219	50875	51444	52128	52933	53616	54362	55243	55983	56764	57736	58794	59684	60675	61605	62533	63329	64318	65403	66309	67158	68007	68969	69773	70413	71173	72076	72853	73610	74352	75190	75887	76784	77498	78259	79131	79821	80483	81061	81810	82554	83264	83954	84625	85147	85846	86497	87193	87760	88349	88899	89456	90024	90617	91271	91875	92500	93173	93842	94431	95035	95600	96129	96672	97206	97723	98269	98903	99441	100013	100600	101142	101584	102171	102601	103066	103582	104278	105016	105728	106465	107163	107887	108606	109338	110172	110920	111792	112626	113468	114362	115253	116126	117089	118041	119061	120072	121122	122105	123081	124312	125419	126405	127240	127869	128425	128601	128732	128826	128907	128978	129042	129097	129215	129308	129431	129473	129521	129566	129598	129627	129664	129702	129736	129761	129785	129807	129826	129842	129865	129879	129888	129895	129903	129910	129918	129918	129941	129955	129966	129975	129982	129990	129994	130002	130009	130014	130018	130023	130027	130029	130033	130035	130037	130043	130047	130050	130052	130053	130059	130061	130067	130072	130074	130081	130086	130097	130109	130118	130125	130139	130152	130166	130174	130187	130205	130222	130243	130256	130291	130314
2	NaN	Algeria	28.03390	1.659600	8	8	12	12	12	12	12	32	32	32	65	65	24	65	29	29	31	31	37	46	61	61	62	90	90	90	113	237	347	405	460	591	601	691	708	783	846	894	1047	1099	1152	1204	1355	1408	1479	1508	1558	1651	1702	1779	1821	1872	1936	1998	2067	2197	2323	2467	2546	2678	2841	2998	3058	3158	3271	3409	3507	3625	3746	3968	4062	4256	4426	4784	4747	4918	5129	5277	5422	5549	5748	5894	6067	6218	6297	6453	6631	6717	6799	6951	7074	7255	7322	7420	7606	7735	7842	7943	8078	8196	8324	8422	8559	8674	8792	8920	9066	9202	9371	9674	9897	10040	10342	10832	11181	11492	11884	12094	12329	12637	13124	13124	13743	14019	14295	14792	15107	15430	15744	16051	16400	16646	16983	17369	17369	18076	18088	18837	19233	19592	20082	20537	20988	21419	21901	22375	22802	23238	23667	24083	24506	24920	25263	25627	26004	26308	26644	27017	27347	27653	27971	28281	28587	28874	29142	29369	29587	29886	30157	30436	30717	30978	31244	31493	31746	32006	32259	32481	32745	32985	33183	33379	33562	33723	33875	34037	34204	34385	34517	34675	34818	34923	35047	35180	35307	35428	35544	35654	35756	35860	35962	36063	36174	36282	36385	36482	36578	36672	36763	36857	36958	37067	37170	37170	37382	37492	37603	37603	37856	37971	38088	38215	38346	38482	38618	38788	38932	39095	39273	39444	39635	39635	40014	40201	40395	40577	40577	41001	41244	41510	41783	42037	42325	42626	42980	42980	43779	44199	44633	45148	45148	46326	46962	47581	48183	48794	49421	50070	50712	51334	51946	52568	53204	53809	54405	54990	55538	56079	56617	57146	57648	58146	58146	59135	59590	60028	60457	60888	61307	61700	62089	62487	62869	63260	63644	64020	64401	64777	65144	65505	65862	66214	66550	66855	67127	67395	67611	67808	67999	68185	68383	68589	68802	69011	69212	69403	69608	69791	69992	70188	70373	70554	70747	70933	71127	71343	71552	71755	71945	72143	72336	72538	72745	72956	73152	73344	73530	73732	73940	74136	74330	74330	74692	74871	75057	75243	75436	75628	75816	75999	76168	76330	76489	76640	76797	76940	77076	77225	77382	77537	77683	77842	77976	78098	78234	78377	78524	78672	78824	78946	79064	79187	79319	79428	79556	79672	79783	79887	79994	80103	80219	80347	80455	80566	80659	80887	80981	81065	81065	81160	81242	81316	81349	81442	81538	81632	81729	81813	81896	81994	82096	82192	82289	82392	82493	82600	82704	82813	82929	83048	83169	83286	83397	83514	83636	83765	83900	84038	84167	84299	84440	84598	84745	84940	85108	85249	85398	85534	85693	85869	86007	86149	86280	86420	86554	86703	86857	87003	87137	87251	87359	87476	87609	87746	87902	88066	88208	88346	88497	88672	88861	89040	89232	89419	89625	89839	90057	90281	90517	90767	90995	91198	91413	91651	91894	92132	92384	92620	92852	93094	93355	93586	93831	94093	94336	94571	94822	95084	95331	95599	95878	96108	96335	96572	96815	97089	97380	97701	98031	98387	98748	99101	99510	99931	100383	100911	101430	102010	102594	103192	103809	104397	104992	105604	106337	107041	107776	108537	109349	109951	110577	111322	112050	112900	113707	114531	115276	116009	116770	117557	118409
3	NaN	Andorra	42.50630	1.521800	1	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	10	10	10	10	16	21	26	31	39	52	58	71	71	128	128	128	169	169	191	205	235	248	282	309	333	344	344	344	385	398	423	468	468	472	493	499	514	521	526	537	545	550	550	568	576	596	604	615	617	624	628	639	639	652	653	653	663	676	676	681	684	692	694	698	733	735	738	741	741	744	751	757	759	780	781	781	781	789	789	791	792	792	792	792	796	797	797	797	799	799	799	799	799	799	800	800	800	800	800	800	802	802	803	803	803	803	803	803	803	803	803	803	803	803	803	803	803	803	803	803	803	804	806	807	807	807	821	825	825	828	839	839	839	839	839	855	858	863	863	863	869	869	875	875	875	875	875	877	877	893	893	902	902	902	908	908	909	909	928	928	928	934	934	938	938	943	943	943	945	945	1054	1054	1164	1164	1164	1199	1199	1203	1203	1263	1263	1263	1265	1265	1432	1432	1540	1540	1540	1615	1615	1715	1715	1814	1814	1814	1928	1928	2011	2011	2057	2057	2057	2273	2273	2470	2470	2729	2729	2729	2957	3029	3144	3260	3377	3475	3475	3548	3627	3734	3858	3858	4043	4248	4332	4405	4488	4585	4675	4675	4747	4830	4965	5055	5127	5239	5290	5358	5405	5503	5542	5649	5710	5710	5794	5873	5940	5988	6066	6130	6171	6238	6293	6367	6452	6505	6598	6629	6629	6706	6706	6819	6875	6919	6963	6997	7028	7073	7106	7171	7203	7252	7288	7318	7360	7384	7432	7463	7463	7517	7548	7585	7615	7615	7724	7724	7724	7724	7930	8070	8091	8116	8116	8154	8154	8349	8399	8474	8537	8588	8652	8724	8774	8851	8942	8986	9045	9093	9206	9252	9313	9395	9444	9492	9533	9610	9674	9732	9781	9833	9868	9911	9965	10022	10066	10101	10146	10170	10206	10245	10285	10319	10356	10394	10429	10446	10475	10501	10560	10564	10584	10599	10626	10661	10685	10708	10708	10754	10775	10796	10795	10861	10883	10904	10925	10952	10973	11014	11050	11082	11111	11149	11172	11204	11244	11276	11315	11365	11401	11428	11474	11523	11570	11616	11692	11732	11770	11825	11890	11932	11989	11989	12105	12159	12203	12203	12285	12334	12375	12423	12458	12491	12519	12561	12590	12650	12684	12684	12753	12793	12818	12884	12900	12936	12962	12995	13021	13070	13104	13104	13155	13155	13155	13211	13234	13234	13234	13234	13234	13234	13234	13263	13381	13405	13416	13416	13416	13458	13479	13507	13527	13527	13527	13527	13557	13557	13569	13578	13591	13591	13591	13618	13626	13633	13640	13650	13650	13650	13665	13665	13688	13694	13697	13697	13697	13697	13717	13720	13721	13721	13721	13721	13721	13752	13757	13760	13770	13770	13770	13787	13796	13796	13829	13844	13844	13844	13897	13930	13930	13988	13988	13988	13988	14077	14113	14113	14180	14210	14210	14210	14296	14348	14380
4	NaN	Angola	-11.20270	17.873900	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	2	2	2	2	2	2	2	4	4	4	5	5	5	5	6	6	6	6	6	6	6	6	6	6	6	7	7	11	11	11	11	11	11	11	11	13	13	13	13	14	14	17	17	17	17	17	17	17	17	18	18	18	18	18	18	18	18	18	18	18	18	18	21	24	24	38	38	40	41	42	61	61	64	64	64	64	66	66	77	77	77	77	81	81	81	81	93	93	97	97	107	108	108	108	117	117	117	117	118	118	118	118	124	124	199	210	221	221	221	221	236	241	242	242	242	266	301	395	437	460	461	476	503	506	520	544	564	567	569	575	577	577	584	628	628	632	667	698	742	804	814	818	877	977	977	1335	1028	1041	1063	1071	1084	1115	1144	1167	1192	1198	1215	1215	1245	1277	1288	1289	1301	1324	1332	1401	1405	1443	1445	1445	1449	1462	1473	1503	1554	1639	1707	1813	1833	1941	2082	2215	2436	2577	2591	2598	2598	2635	2685	2716	2743	2744	2761	2801	2928	3012	3022	3030	3031	3037	3040	3305	3384	3461	3508	3530	3647	3693	3736	4107	4523	4920	5172	5230	5266	5350	5626	5647	5899	5927	6036	6125	6250	6326	6345	6444	6523	6582	6623	7062	7117	7273	7346	7351	7444	7517	7617	7697	7763	7763	7851	7932	8139	8244	8299	8335	8338	8353	8470	8579	8679	8798	8841	8898	8924	8990	9194	9266	9345	9518	9592	9695	9729	9729	9729	9921	9976	10354	10354	10627	10859	11044	11146	11189	11223	11266	11376	11477	11955	12712	13205	13872	14825	15512	15631	16008	16120	16225	16347	16677	16822	16921	17176	17223	17249	17266	17327	17388	17602	17692	17918	18015	18035	18180	18232	18335	18381	18431	18475	18540	18596	18623	18687	18710	18786	18790	18795	18884	18929	18951	18972	18991	19005	19013	19190	19207	19221	19238	19307	19315	19322	19400	19410	19509	19553	19624	19640	19647	19657	19677	19761	19827	19835	19848	19850	19948	19971	20028	20032	20065	20068	20073	20090	20099	20172	20190	20250	20269	20289	20380	20446	20493	20508	20867	20871	20879	21452	21489	21545	21557	21589	21890	22058	22093	22115	22144	22175	22203	22576	22597	22600	22647	22882	22901	23089	23092	23092	23288	23341	23584	23606	23876	23913	23913	24190	24190	24492	24503	24698	24713	24717	24772	25145	25187	25629	25650	25703	25715	25995	26013	26458	26483	26513	26775	26778	27087	27204	27467	27529	27577	27646	27766	28079	28190	28264	28646	28802	28866	28880	29329	29368	29553	29960	30101	30207	30282	30359	30775	31003	31105	31569	31589	31676	31782	32003	32322	32340	32605	32696	32791	32819	33079	33242	33271	33375	33514	33669	33739	34019	34047	34100	34169	34298	34327	34357	34500	34584	34620	34724	34732	34755	34790	34857	34893	35082	35284	35423	35474	35686	35742	35964	36025	36708	37255	37397	38360	39389	39582

	states	region	Population	Overall CCVI Index	Age	Epidemiological	Fragility	Health System	Population Density	Socio-Economic	Transport Availability	Acute IHR
0	FCT	North Central	4865000	0.3	0.0	0.9	0.4	0.6	0.9	0.6	0.2	0.79
1	Plateau	North Central	4766000	0.4	0.5	0.4	0.8	0.3	0.3	0.5	0.3	0.93
2	Kwara	North Central	3524000	0.3	0.4	0.3	0.2	0.4	0.2	0.6	0.7	0.93
3	Nassarawa	North Central	2783000	0.1	0.3	0.5	0.9	0.0	0.1	0.6	0.5	0.85
4	Niger	North Central	6260000	0.6	0.0	0.6	0.3	0.7	0.1	0.8	0.8	0.84

	states	Initial_budget (Bn)	Revised_budget (Bn)
0	Abia	136.60	102.70
1	Adamawa	183.30	139.31
2	Akwa-Ibom	597.73	366.00
3	Anambra	137.10	112.80
4	Bauchi	167.20	128.00

Task 1 - Data Collection¶

A - NCDC Website scraping¶

B - John Hopkins Data Repository¶

C - External Data¶

Task 2 - View the data¶

Task 3 - Data Cleaning and Preparation¶

Checking for variation in state names for the two data sets.¶

Getting Daily data for Deaths, Confirmed and Recovered Cases in Nigeria¶

Task 4 - Analysis¶

Create 7 day Moving Average for Confirmed, recovered and Death cases to properly visualize the data.¶

Merge Covid External And Data DataFrames to provide more analysis.¶

Check correlation between variables¶

Analysis on the Budget Data.¶

Analysis Of Geographical Data¶

Map to Show Lab Confirmed Cases across all States¶

Map to show deaths across states¶

	states	lab_confirmed_cases	cases_on_admission	discharged	deaths
0	Lagos	104,014	871	102,372	771
1	FCT	29,464	143	29,072	249
2	Rivers	18,044	89	17,800	155
3	Kaduna	11,576	11	11,476	89
4	Oyo	10,332	3	10,127	202

	states	lab_confirmed_cases	cases_on_admission	discharged	deaths
0	Lagos	104014	871	102372	771
1	FCT	29464	143	29072	249
2	Rivers	18044	89	17800	155
3	Kaduna	11576	11	11476	89
4	Oyo	10332	3	10127	202

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deaths	NaN	Nigeria	9.082	8.6753	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	1	1	1	2	2	2	2	4	4	5	5	6	6	7	7	10	10	10	11	12	13	17	19	21	22	22	28	31	32	35	40	40	44	51	58	68	85	87	93	98	103	107	117	128	143	150	158	164	167	171	176	182	191	192	200	211	221	221	226	233	249	254	259	261	273	287	299	314	315	323	333	342	354	361	365	382	387	399	407	420	424	455	469	475	487	506	518	525	533	542	549	554	558	565	573	590	603	616	628	634	645	654	669	684	689	709	724	740	744	754	760	769	772	778	789	801	805	813	833	845	856	858	860	868	873	878	879	883	888	896	910	927	930	936	942	945	950	956	956	966	973	974	975	977	981	985	992	996	997	1002	1004	1007	1010	1011	1011	1011	1013	1013	1023	1027	1048	1051	1054	1057	1061	1067	1070	1075	1076	1078	1082	1083	1088	1091	1093	1094	1095	1098	1100	1100	1102	1102	1103	1106	1108	1111	1111	1112	1112	1112	1113	1113	1113	1113	1113	1113	1113	1115	1115	1115	1116	1116	1116	1119	1123	1125	1125	1125	1125	1127	1129	1129	1130	1132	1135	1139	1141	1144	1144	1146	1147	1151	1155	1155	1155	1155	1154	1158	1160	1162	1162	1163	1163	1163	1163	1163	1163	1165	1165	1166	1167	1168	1169	1169	1169	1171	1171	1173	1173	1176	1177	1179	1179	1180	1180	1181	1182	1184	1190	1190	1194	1197	1197	1200	1200	1201	1212	1218	1221	1227	1231	1236	1242	1246	1247	1254	1264	1267	1278	1289	1294	1302	1311	1318	1319	1324	1330	1342	1350	1358	1361	1373	1382	1405	1413	1420	1435	1449	1464	1478	1485	1490	1502	1504	1507	1522	1543	1547	1577	1578	1586	1607	1613	1618	1632	1641	1647	1667	1673	1694	1702	1710	1734	1747	1752	1761	1777	1787	1803	1813	1831	1839	1862	1874	1885	1891	1902	1905	1907	1915	1923	1939	1951	1954	1964	1969	1982	1988	1993	2001	2009	2013	2013	2016	2018	2027	2027	2027	2030	2030	2030	2031	2031	2036	2039	2041	2048	2049	2056	2057	2058	2058	2058	2058	2058	2058	2058	2058	2059	2060	2060	2061	2061	2061	2061	2061	2061	2061	2061	2061	2061	2061	2061	2061	2062	2062	2063	2063	2063	2063	2063	2063	2063	2063	2065	2065	2065	2065	2065	2065	2065	2066	2066	2066	2066	2066	2067	2067	2067	2067	2067	2067	2067	2067	2071	2071	2071	2071	2071	2071	2099	2099	2099	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2117	2118	2118	2118	2118	2119	2119	2119	2119	2120	2120	2121	2121	2121	2121	2122	2122	2122	2122	2122	2122	2124	2124	2125	2125	2126	2126	2126	2127	2128	2128	2128	2130	2130	2132	2132	2134	2134	2139	2141	2149	2149	2149	2160	2163	2167	2178	2181	2185	2187	2192	2194	2195	2200	2211	2219	2219	2223	2229	2229	2244	2247	2247	2268	2276	2281	2288	2298	2308	2361	2454	2455	2469	2480	2488	2495	2522	2552	2556	2573	2578	2585	2588	2590	2598	2619	2637	2640	2640	2649	2654	2655	2661	2664	2666	2668	2671	2673	2677	2690	2695	2701	2721	2724	2724	2724	2724	2731	2731	2742	2743	2745	2747	2756	2756	2761	2761	2769	2804	2837	2838	2838	2840	2850	2855	2856	2882	2884	2884	2886	2892	2895	2895	2896	2898	2899	2900	2902	2902	2905	2906	2906	2914	2922	2933	2949	2960	2968	2968	2968	2973	2973	2973	2973	2974	2974	2974	2974	2975	2975	2975	2975	2976	2977	2978	2978	2980	2980	2980	2980	2980	2980	2980	2981	2981	2981	2981	2983	2983	2983	2984	2984	2984	2985	2985	2991	2991	2993	3014	3022	3024	3027	3030	3030	3030	3033	3033	3045	3053	3058	3066	3070	3071	3077	3085	3086	3092	3092	3092	3095	3103	3110	3116	3117	3117	3124	3124	3124	3126	3133	3134	3134	3134	3135	3135	3136	3136	3136	3136	3136	3139	3139	3139	3139	3139	3139	3139	3141	3141	3141	3141	3141	3141	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3142	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3143	3148	3148	3148	3148	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3144	3146	3146	3146	3146	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3147	3148	3148	3148	3148	3148	3148	3148	3148	3148	3148	3148	3148	3148	3148	3148	3148	3154	3154	3154	3154	3154	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155	3155
recovered	NaN	Nigeria	9.082	8.6753	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	2	2	2	2	2	3	3	3	8	8	9	20	25	25	33	35	44	44	51	58	70	85	91	99	128	152	159	166	170	188	188	197	197	208	222	239	255	255	307	319	351	351	400	417	481	534	601	679	745	778	902	959	1070	1180	1320	1472	1594	1644	1734	1840	1907	2007	2174	2263	2311	2385	2501	2592	2697	2856	3007	3122	3240	3329	3535	3696	3826	3959	4040	4206	4351	4494	4891	5101	5220	5349	5623	5967	6307	6581	6718	6879	7109	7338	7613	7822	8253	8625	9007	9402	9746	10152	10801	11069	11462	11665	11828	12108	12373	12546	12795	13103	13447	13671	13792	13999	14292	14633	14938	15105	15333	15677	15815	16061	16559	16948	17374	18203	18764	19004	19270	19565	20087	20308	20663	31851	32165	32430	32637	33044	33186	33346	33609	33943	34309	35998	36290	36497	36834	37051	37304	37569	37885	38767	38945	39257	39964	40281	40726	41017	41314	41513	41638	42010	42439	42627	42816	42922	43013	43231	43334	43610	43810	43998	44088	44152	44337	44430	47872	48092	48305	48431	48569	48674	48836	48985	49098	49606	49722	49794	49895	49937	50358	50452	50593	50718	50768	50951	51308	51403	51551	51614	51711	51735	51943	52006	52143	52194	52304	56557	56611	56697	56797	56880	56985	57190	57285	57465	57571	57916	58095	58249	58430	58675	58790	59328	59634	59675	59748	59844	59884	59910	60069	60333	60737	60790	60936	61029	61073	61162	61337	61457	61573	61782	61884	62076	62241	62311	62493	62585	62686	62819	63055	63282	63430	63839	64291	64467	64650	64774	64947	65110	65242	65474	65722	65850	66090	66314	66494	66775	67110	67484	67784	68303	68493	68879	69274	69651	70248	70495	71034	71357	71937	73322	73713	74373	74789	75044	75699	76396	77299	77982	78552	79417	80030	80491	81574	82555	83830	84535	85367	89317	89939	91200	92336	93646	94130	95901	97228	98359	99276	100365	100853	102780	103712	104989	106275	107551	108657	110449	111639	112557	113525	114635	115755	116947	118012	118866	120399	120838	123009	124483	125722	126417	127524	128005	128619	129300	129943	130818	131699	132544	133256	133768	133904	134551	135812	136335	137025	137645	137890	138502	139056	139983	142404	144059	144714	145399	145752	146072	146395	146890	147581	147775	147899	148125	148530	148726	149882	149986	150205	150308	150466	151532	151648	151708	151835	151853	151998	152045	153630	153788	154005	154073	154098	154107	154177	154225	154270	154285	154304	154325	154332	154384	154406	154441	154578	154643	154687	154926	154963	155012	155021	155041	155101	155101	155109	155371	155371	155403	155424	155454	156250	156297	156318	156358	156374	156387	156399	156412	156413	156415	156415	156456	156459	156462	156468	156476	156492	156528	156529	156535	156546	156557	156558	158781	159935	159946	162521	162584	162994	163096	163190	163259	163331	163331	163430	163436	163463	163469	163483	163528	163535	163540	163550	163557	163797	163913	163917	163933	163937	163946	163949	163984	163985	164244	164273	164369	164378	164382	164400	164405	164408	164415	164423	164431	164439	164476	164623	164652	164662	164666	164672	164699	164720	164733	164733	164772	164772	164788	164789	164798	164837	164886	164930	164978	164994	165005	165037	165122	165208	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
confirmed	NaN	Nigeria	9.082	8.6753	1	1	1	1	1	1	1	1	1	1	2	2	2	2	2	2	2	2	3	8	8	12	22	30	40	44	51	65	70	89	111	131	135	174	184	210	214	232	238	254	276	288	305	318	323	343	373	407	442	493	542	627	665	665	873	981	1095	1182	1273	1337	1532	1728	1932	2170	2388	2558	2802	2950	3145	3526	3912	4151	4399	4641	4787	4971	5162	5450	5621	5959	6175	6401	6677	7016	7261	7526	7839	8068	8344	8733	8915	9302	9855	10162	10578	10819	11166	11516	11844	12233	12486	12801	13464	13873	14554	15181	15682	16085	16658	17148	17735	18480	19147	19808	20244	20919	21371	22020	22614	23298	24077	24567	25133	25694	26484	27110	27564	28167	28711	29286	29789	30249	30748	31323	31987	32558	33153	33616	34259	34854	35454	36107	36663	37225	37801	38344	38948	39539	39977	40532	41180	41804	42208	42689	43151	43537	43841	44129	44433	44890	45244	45687	46140	46577	46867	47290	47743	48116	48445	48770	49068	49485	49895	50488	50964	51304	51905	52227	52548	52800	53021	53317	53477	53727	53865	54008	54247	54463	54588	54743	54905	55005	55160	55456	55632	55829	56017	56177	56256	56388	56478	56604	56735	56956	57145	57242	57437	57613	57724	57849	58062	58198	58324	58460	58647	58848	59001	59127	59287	59345	59465	59583	59738	59841	59992	60103	60266	60430	60655	60834	60982	61194	61307	61440	61558	61630	61667	61805	61882	61930	61992	62111	62224	62371	62521	62691	62853	62964	63036	63173	63328	63508	63731	63790	64090	64184	64336	64516	64728	64884	64996	65148	65305	65457	65693	65839	65982	66228	66383	66439	66607	66805	66974	67220	67330	67412	67557	67838	67960	68303	68627	68937	69255	69645	70195	70669	71344	72140	72757	73175	73374	74132	75062	76207	77013	77933	78434	78790	79789	80922	81963	82747	83576	84414	84811	85560	86576	87607	88587	89163	90080	91351	92705	94369	95934	97478	99063	100087	101331	102601	103999	105478	107345	108943	110387	112004	113305	114691	116655	118138	120602	121566	122996	124299	126160	127024	128674	130557	131242	131918	133552	134690	136030	137654	139242	139748	140391	141447	142578	143516	144521	145664	146184	146928	148296	149369	150246	150908	151553	152074	152616	153187	153842	154476	155076	155417	155657	156017	156496	156960	157671	158042	158237	158506	158906	159252	159646	159933	160332	160537	160657	160895	161074	161261	161409	161539	161651	161737	161868	162076	162178	162275	162388	162489	162593	162641	162762	162891	162997	163063	163113	163195	163330	163388	163498	163581	163652	163736	163799	163837	163911	164000	164080	164147	164207	164233	164303	164423	164488	164588	164633	164684	164719	164756	164912	164993	165055	165110	165110	165153	165199	165215	165273	165301	165340	165370	165419	165468	165515	165559	165612	165661	165702	165709	165778	165778	165852	165901	165944	165979	166019	166061	166098	166146	166191	166254	166285	166315	166518	166534	166560	166682	166730	166756	166767	166816	166918	166982	166982	167051	167059	167066	167078	167095	167103	167142	167155	167206	167206	167292	167331	167375	167401	167430	167465	167467	167532	167543	167618	167692	167732	167803	167859	167909	168000	168110	168256	168442	168540	168552	168713	168867	168915	169074	169206	169329	169532	169678	169884	169884	170306	170306	170895	171111	171324	171728	172263	172821	173411	173908	174315	174759	175264	176011	176577	177142	177615	178086	178508	179118	179908	180661	181297	181962	182503	183087	183444	183444	185267	185571	185571	187023	187588	188243	188880	189715	190333	190983	191345	191805	192431	193013	193644	194088	195052	195511	195890	196487	197046	197773	198239	198786	199151	199538	200057	200356	200356	201294	201630	201798	202191	202704	203081	203514	203991	204201	204456	204752	205047	205484	205779	205940	206064	206138	206279	206561	206561	207167	207479	207618	207694	207978	207979	208404	208404	208797	209173	209298	209387	209546	209713	209960	210136	210295	210460	211171	211330	211496	211678	211798	211887	211961	212051	212150	212359	212446	212511	212627	212713	212765	212829	212894	212947	213076	213127	213147	213177	213177	213403	213464	213487	213532	213589	213589	213677	213677	213883	213883	213924	213982	214113	214218	214270	214270	214513	214567	214622	214789	214896	215164	215164	216451	217063	217481	217481	218596	220020	221071	222655	222655	223483	225255	225255	231413	233353	234709	236014	237561	238420	239019	240387	241513	241513	242877	242877	244120	244548	245404	246195	247009	247775	248312	248732	249154	249586	250009	250009	250628	250929	251178	251341	251571	251571	251930	251959	252187	252428	252678	252753	252753	252912	253001	253023	253181	253340	253405	253405	253540	253685	253727	253780	253838	253875	253875	253923	253978	254016	254016	254124	254137	254137	254221	254243	254243	254293	254352	254352	254428	254428	254501	254525	254560	254570	254598	254606	254637	254637	254640	254659	254777	254777	254861	254894	254953	254953	254989	255001	255001	255092	255103	255103	255103	255103	255190	255244	255244	255244	255296	255296	255341	255341	255415	255415	255468	255468	255468	255468	255516	255516	255575	255575	255606	255606	255633	255663	255633	255646	255646	255648	255648	255648	255670	255670	255679	255685	255685	255685	255685	255685	255685	255716	255716	255716	255753	255753	255766	255766	255766	255766	255766	255766	255766	255802	255802	255836	255836	255859	255859	255859	255859	255889	255924	255924	255937	255937	255937	255972	255972	256004	256028	256028	256028	256028	256028	256028	256113	256113	256148	256148	256148	256227	256227	256264	256264	256352	256352	256352	256404	256404	256467	256467	256573	256573	256573	256711	256711	256711	256711	256958	256958	256958	256958	256958	257290	257290	257637	257637	257637	257637	257637	257637	257637	258517	258517	258517	258874	258874	258934	258934	259007	259007	259007	259485	259485	259720	259720	260339	260339	260339	260764	260764	260977	260977	260977	260977	260977	261473	261473	261473	261473	261473	261885	261885	261885	261885	262402	262402	262520	262520	262520	262664	262664	262748	262748	262912	262912	262912	263090	263090	263322	263322	263407	263407	263407	263526	263526	263694	263694	263867	263867	263867	264014	264014	264299	264299	264299	264450	264450	264617	264617	264744	264744	264933	264933	264933	265008	265008	265090	265090	265186	265186	265186	265316	265316	265382	265382	265431	265431	265431	265505	265505	265741	265741	265816	265816	265816	265816	265816	265816	265816	265937

	dates	confirmed
0	2020-01-23	0
1	2020-01-24	0
2	2020-01-25	0
3	2020-01-26	0
4	2020-01-27	0
5	2020-01-28	0
6	2020-01-29	0
7	2020-01-30	0
8	2020-01-31	0
9	2020-02-01	0
10	2020-02-02	0
11	2020-02-03	0
12	2020-02-04	0
13	2020-02-05	0
14	2020-02-06	0
15	2020-02-07	0
16	2020-02-08	0
17	2020-02-09	0
18	2020-02-10	0
19	2020-02-11	0
20	2020-02-12	0
21	2020-02-13	0
22	2020-02-14	0
23	2020-02-15	0
24	2020-02-16	0
25	2020-02-17	0
26	2020-02-18	0
27	2020-02-19	0
28	2020-02-20	0
29	2020-02-21	0
30	2020-02-22	0
31	2020-02-23	0
32	2020-02-24	0
33	2020-02-25	0
34	2020-02-26	0
35	2020-02-27	0
36	2020-02-28	1
37	2020-02-29	1
38	2020-03-01	1
39	2020-03-02	1
40	2020-03-03	1
41	2020-03-04	1
42	2020-03-05	1
43	2020-03-06	1
44	2020-03-07	1
45	2020-03-08	1
46	2020-03-09	2
47	2020-03-10	2
48	2020-03-11	2
49	2020-03-12	2

	dates	deaths	confirmed	daily_confirmed_count
805	2022-04-07	3142	255575	59.0
806	2022-04-08	3142	255575	0.0
807	2022-04-09	3142	255606	31.0
808	2022-04-10	3142	255606	0.0
809	2022-04-11	3142	255633	27.0
810	2022-04-12	3142	255663	30.0
811	2022-04-13	3142	255633	-30.0

	dates	deaths	recovered	confirmed	daily_death_count	daily_recovered_count	daily_confirmed_count
290	2020-11-08	1154	59910	64090	-1.0	26.0	300.0
869	2022-06-10	3144	0	256264	-4.0	0.0	0.0

	dates	deaths	confirmed	daily_death_count	daily_confirmed_count
865	2022-06-06	3148	256148	5.0	0.0
866	2022-06-07	3148	256227	0.0	79.0
867	2022-06-08	3148	256227	0.0	0.0
868	2022-06-09	3148	256264	0.0	37.0
869	2022-06-10	3144	256264	-4.0	0.0

	dates	deaths	recovered	confirmed	daily_death_count	daily_recovered_count	daily_confirmed_count
289	2020-11-07	1155	59884	63790	0.0	40.0	59.0
290	2020-11-08	1154	59910	64090	-1.0	26.0	300.0
291	2020-11-09	1158	60069	64184	4.0	159.0	94.0
292	2020-11-10	1160	60333	64336	2.0	264.0	152.0
293	2020-11-11	1162	60737	64516	2.0	404.0	180.0
294	2020-11-12	1162	60790	64728	0.0	53.0	212.0

	states	Initial_budget (Bn)	Revised_budget (Bn)	difference	percent
8	Cross River	1100.00	147.10	952.90	86.63
23	Lagos	1680.00	920.50	759.50	45.21
15	Imo	197.60	108.30	89.30	45.19
31	Rivers	530.80	300.40	230.40	43.41
21	Kogi	176.00	102.00	74.00	42.05
24	Nasarawa	108.40	62.96	45.44	41.92
2	Akwa-Ibom	597.73	366.00	231.73	38.77
26	Ogun	449.90	280.00	169.90	37.76
6	Benue	189.00	119.00	70.00	37.04
25	Niger	155.00	98.00	57.00	36.77

	states	Initial_budget (Bn)	Revised_budget (Bn)	difference	percent
19	Katsina	244.00	213.0	31.00	12.70
13	Enugu	169.56	146.4	23.16	13.66
17	Kaduna	259.25	223.6	35.65	13.75
3	Anambra	137.10	112.8	24.30	17.72
14	Gombe	130.83	107.4	23.43	17.91
29	Oyo	213.00	174.0	39.00	18.31
16	Jigawa	152.92	124.0	28.92	18.91
27	Ondo	187.80	151.4	36.40	19.38
34	Yobe	108.00	86.0	22.00	20.37
4	Bauchi	167.20	128.0	39.20	23.44

	admin1Name	admin1Pcod	admin1RefN	admin1AltN	admin1Al_1	admin0Name	admin0Pcod	date	validOn	validTo	Shape_Leng	Shape_Area	geometry
0	Abia	NG001	Abia	None	None	Nigeria	NG	2016-11-29	2016-12-15	None	4.695135	0.396543	MULTIPOLYGON (((7.38681 6.03667, 7.38729 6.036...
1	Adamawa	NG002	Adamawa	None	None	Nigeria	NG	2016-11-29	2016-12-15	None	11.525443	3.113007	MULTIPOLYGON (((13.62129 10.94823, 13.62592 10...
2	Akwa Ibom	NG003	Akwa Ibom	None	None	Nigeria	NG	2016-11-29	2016-12-15	None	5.263830	0.549476	MULTIPOLYGON (((8.34482 4.61140, 8.34496 4.609...
3	Anambra	NG004	Anambra	None	None	Nigeria	NG	2016-11-29	2016-12-15	None	3.595960	0.392661	MULTIPOLYGON (((6.93254 6.71090, 6.93167 6.698...
4	Bauchi	NG005	Bauchi	None	None	Nigeria	NG	2016-11-29	2016-12-15	None	13.952005	4.011018	MULTIPOLYGON (((10.75125 12.46148, 10.75615 12...

	states	Shape_Length	Shape_Area	geometry
0	Abia	4.695135	0.396543	MULTIPOLYGON (((7.38681 6.03667, 7.38729 6.036...
1	Adamawa	11.525443	3.113007	MULTIPOLYGON (((13.62129 10.94823, 13.62592 10...
2	Akwa Ibom	5.263830	0.549476	MULTIPOLYGON (((8.34482 4.61140, 8.34496 4.609...
3	Anambra	3.595960	0.392661	MULTIPOLYGON (((6.93254 6.71090, 6.93167 6.698...
4	Bauchi	13.952005	4.011018	MULTIPOLYGON (((10.75125 12.46148, 10.75615 12...

	states	Shape_Length	Shape_Area	geometry
0	Abia	4.695135	0.396543	MULTIPOLYGON (((7.38681 6.03667, 7.38729 6.036...
1	Adamawa	11.525443	3.113007	MULTIPOLYGON (((13.62129 10.94823, 13.62592 10...
2	Akwa Ibom	5.263830	0.549476	MULTIPOLYGON (((8.34482 4.61140, 8.34496 4.609...
3	Anambra	3.595960	0.392661	MULTIPOLYGON (((6.93254 6.71090, 6.93167 6.698...
4	Bauchi	13.952005	4.011018	MULTIPOLYGON (((10.75125 12.46148, 10.75615 12...
5	Bayelsa	5.046708	0.776768	MULTIPOLYGON (((6.55283 5.37988, 6.56198 5.379...
6	Benue	9.408080	2.578363	MULTIPOLYGON (((8.52442 8.15727, 8.54240 8.148...
7	Borno	13.714364	5.987849	MULTIPOLYGON (((13.35885 13.71261, 13.36207 13...
8	Cross River	8.779796	1.711218	MULTIPOLYGON (((8.56068 4.79847, 8.55944 4.798...
9	Delta	7.372526	1.394082	MULTIPOLYGON (((6.66892 6.50123, 6.67111 6.484...
10	Ebonyi	4.489355	0.518050	MULTIPOLYGON (((8.24431 6.78560, 8.24976 6.775...
11	Edo	7.889425	1.595809	MULTIPOLYGON (((6.13357 7.55208, 6.13835 7.550...
12	Ekiti	3.395633	0.471634	MULTIPOLYGON (((5.50593 8.01869, 5.50872 8.017...
13	Enugu	4.319893	0.624323	MULTIPOLYGON (((7.54536 7.00125, 7.54930 6.991...
14	FCT	3.498412	0.607222	MULTIPOLYGON (((7.67239 9.41128, 7.71959 9.346...
15	Gombe	5.955286	1.438747	MULTIPOLYGON (((11.07149 11.31249, 11.07479 11...
16	Imo	2.878088	0.414097	MULTIPOLYGON (((7.26575 5.93081, 7.26607 5.927...
17	Jigawa	11.771497	1.928873	MULTIPOLYGON (((10.23002 13.01060, 10.23084 13...
18	Kaduna	12.613678	3.645639	MULTIPOLYGON (((8.16953 11.48727, 8.16955 11.4...
19	Kano	8.244195	1.685607	MULTIPOLYGON (((8.30528 12.58803, 8.31002 12.5...
20	Katsina	9.105637	1.991947	MULTIPOLYGON (((7.81802 13.33042, 7.82082 13.3...
21	Kebbi	14.968981	3.035227	MULTIPOLYGON (((4.25355 13.26045, 4.26682 13.2...
22	Kogi	10.476383	2.368882	MULTIPOLYGON (((6.51270 8.39867, 6.52740 8.375...
23	Kwara	12.046963	2.766244	MULTIPOLYGON (((3.73068 10.06829, 3.73651 10.0...
24	Lagos	4.287770	0.300166	MULTIPOLYGON (((3.32387 6.67388, 3.32879 6.673...
25	Nassarawa	9.537188	2.197927	MULTIPOLYGON (((7.99731 9.31436, 8.00084 9.306...
26	Niger	18.921559	5.930956	MULTIPOLYGON (((4.92994 11.35723, 4.93396 11.3...
27	Ogun	9.649774	1.364021	MULTIPOLYGON (((2.84613 7.92988, 2.85077 7.929...
28	Ondo	7.751109	1.233546	MULTIPOLYGON (((5.92604 7.73182, 5.92513 7.728...
29	Osun	4.660140	0.704549	MULTIPOLYGON (((4.94975 8.05548, 4.95674 8.053...
30	Oyo	8.624586	2.264918	MULTIPOLYGON (((4.21046 8.97003, 4.25339 8.966...
31	Plateau	8.575527	2.180996	MULTIPOLYGON (((8.79339 10.38465, 8.79925 10.3...
32	Rivers	5.814545	0.830196	MULTIPOLYGON (((6.64358 5.70171, 6.64836 5.699...
33	Sokoto	10.503159	2.679547	MULTIPOLYGON (((5.51464 13.89442, 5.52912 13.8...
34	Taraba	13.696255	4.802474	MULTIPOLYGON (((10.83822 9.61847, 10.84855 9.6...
35	Yobe	11.096937	3.726688	MULTIPOLYGON (((11.22181 13.37400, 11.25518 13...
36	Zamfara	9.466144	2.782855	MULTIPOLYGON (((6.84870 13.08240, 6.87310 13.0...